diff options
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch1.ipynb | 85 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch10.ipynb | 130 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch11.ipynb | 188 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch12.ipynb | 208 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch13.ipynb | 104 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch14.ipynb | 284 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch2.ipynb | 144 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch4.ipynb | 188 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch5.ipynb | 385 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch6.ipynb | 197 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch7.ipynb | 610 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch8.ipynb | 561 | ||||
| -rwxr-xr-x | Basic_Electronics_and_Linear_Circuits/ch9.ipynb | 254 |
13 files changed, 0 insertions, 3338 deletions
diff --git a/Basic_Electronics_and_Linear_Circuits/ch1.ipynb b/Basic_Electronics_and_Linear_Circuits/ch1.ipynb deleted file mode 100755 index 6ff156a7..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch1.ipynb +++ /dev/null @@ -1,85 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:d40864745b0958ff90d45e29ecc4874d2fd0d20b38ed09535ff46977537fd224" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter no. 1: Introduction To Electronics" - ] - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Example 1.1 Page no.8" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "A=4 #NUMERICAL CODE FOR BAND YELLOW\n", - "B=7 #NUMERICAL CODE FOR BAND VIOLET\n", - "C=3 #NUMERICAL CODE FOR BAND ORANGE\n", - "D=5 #TOLERANCE VALUE FOR BAND GOLD i.e. 5%\n", - "\n", - "#Resistor Value Calculation\n", - "R=(A*10+B)*10**C\n", - "#Tolerance Value Calulation\n", - "T=D*R/100;\n", - "R1=R-T;\n", - "R2=R+T;\n", - "\n", - "# Results\n", - "print \"Therefore thr resistance should be within the range \", R1*10**(-3) ,\"kohm\",\"and\", R2*10**(-3),\"kohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 1.2 Page no.8" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "A=8 #NUMERICAL CODE FOR BAND GRAY\n", - "B=6 #NUMERICAL CODE FOR BAND BLUE\n", - "C=-1 #NUMERICAL CODE FOR BAND GOLD\n", - "D=5 #TOLERANCE VALUE FOR BAND GOLD i.e. 5%\n", - "#Resistor Value Calculation\n", - "R=(A*10+B)*10**C\n", - "#Tolerance Value Calulation\n", - "T=D*R/100\n", - "R1=R-T\n", - "R2=R+T\n", - "# Results \n", - "print \"Range of Values of the Resistor is between \",R1,\"ohm\",\"and\",R2,\"ohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch10.ipynb b/Basic_Electronics_and_Linear_Circuits/ch10.ipynb deleted file mode 100755 index 1268374a..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch10.ipynb +++ /dev/null @@ -1,130 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:c0e331b614f072bb0c21b302f0e54b6a8366fa46ba53ae4810b072360f344e0d" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 10: Power Amplifiers" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 10.1 Page No.345" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "RL=16 # Ohms, load resistance\n", - "RLd=10000.0 # Ohms ,effective load resistance\n", - "\n", - "#Calculation\n", - "import math\n", - "N12=math.sqrt(RLd/RL) #N12=N1/N2\n", - "\n", - "# Result\n", - "print \" The Transformer Turns Ratio is N1/N2\",N12,\":1\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Transformer Turns Ratio is N1/N2 25.0 :1\n" - ] - } - ], - "prompt_number": 3 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 10.2 Page No.345" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "#Given Circuit Data\n", - "Rl=8.0 #Ohms, load resistance\n", - "N12=15.0 #N12=N1/N2, transformer turns ratio\n", - "\n", - "#Calculation\n", - "Rld=(N12)**2*Rl #effective resistance\n", - "\n", - "# Result\n", - "print \" The Effective Resistance seen looking into the Primary, Rld = \",Rld/10**3,\"k ohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 10.3 Page No.353" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "I1=15 #A\n", - "I2=1.5 #A\n", - "I3=1.2 #A\n", - "I4=0.5 #A\n", - "\n", - "#Calculation\n", - "D2=(I2/I1)*100 #percentage harmonic distribution of component 2\n", - "D3=(I3/I1)*100 #percentage harmonic distribution of component 3\n", - "D4=(I4/I1)*100 #percentage harmonic distribution of component 4\n", - "\n", - "#Result\n", - "print \" The Second Harmonic Distortion is, D2 = percent .\",D2\n", - "print \" The Third Harmonic Distortion is, D3 = percent .\",D3\n", - "print \" The Fourth Harmonic Distortion is, D4 = percent .\",round(D4,2)\n", - "\n", - "#(b)\n", - "import math\n", - "P1=1 #say\n", - "\n", - "#Calculation\n", - "D=math.sqrt(D2**2+D3**2+D4**2) #Distortion Factor\n", - "P=(1+(D/100)**2)*P1\n", - "Pi=((P-P1)/P1)*100\n", - "\n", - "#Result\n", - "print \"The Percentage Increase in Power because of Distortion is, Pi (in percent)= \",round(Pi,2)" - ], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch11.ipynb b/Basic_Electronics_and_Linear_Circuits/ch11.ipynb deleted file mode 100755 index dd06f959..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch11.ipynb +++ /dev/null @@ -1,188 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:42316ce336a06a4afe76966dd3df12fd0f55e47e7182329e33e900184918fde7" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 11: Tuned Voltage mplifiers" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 11.1 Page No.374" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "C=300*10**(-12) #F, capacitance\n", - "L=220*10**(-6) #H, inductance\n", - "R=20.0 #Ohms, resistance\n", - "\n", - "#Calculation\n", - "import math\n", - "fr=1/(2*math.pi*math.sqrt(L*C)) #resonant frequency\n", - "#result\n", - "print \" The Resonant Frequency, fr = \",round(fr/10**3,0),\"khz\"\n", - "\n", - "#(b) find The Impedance at Resonance\n", - "#Calculation\n", - "Rr=R\n", - "#result\n", - "print \" The Impedance at Resonance, Rr = \",Rr,\"ohm\"\n", - "\n", - "#(c) find The Current at Resonance\n", - "V=10.0 #V, voltage\n", - "#Calculation\n", - "I=V/R\n", - "#result\n", - "print \" The Current at Resonance, I = \",I,\"A\"\n", - "\n", - "#(d)\n", - "#Calculation\n", - "fr=1/(2*math.pi*math.sqrt(L*C))\n", - "I=V/R\n", - "Xl=2*math.pi*fr*L #reactance of inductor\n", - "Vl=I*Xl # Voltage across the Inductance\n", - "Xc=1/(2*math.pi*fr*C) #reactance of capacitance\n", - "Vc=I*Xc # Voltage across the Capacitance,\n", - "Vr=I*R #Voltage across the Resistance\n", - "\n", - "#result\n", - "print \" Voltage across the Inductance, Vl = \",round(Vl,0),\"V\"\n", - "print \" Voltage across the Capacitance, Vc = \",round(Vc,0),\"V\"\n", - "print \" Voltage across the Resistance, Vr = \",round(Vr,0),\"V\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Resonant Frequency, fr = 620.0 khz\n", - " The Impedance at Resonance, Rr = 20.0 ohm\n", - " The Current at Resonance, I = 0.5 A\n", - " Voltage across the Inductance, Vl = 428.0 V\n", - " Voltage across the Capacitance, Vc = 428.0 V\n", - " Voltage across the Resistance, Vr = 10.0 V\n" - ] - } - ], - "prompt_number": 2 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 11.2 Page No.378" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "C=100*10**(-12) #F\n", - "L=100*10**(-6) #H\n", - "R=10 #Ohms\n", - "V=100 #V\n", - "\n", - "#Calculation\n", - "import math\n", - "fr=1/(2*math.pi*math.sqrt(L*C)) #Hz, resonant frequency\n", - "Xl=2*math.pi*fr*L #ohm, inductive reactance\n", - "Il=V/Xl #A, current in inductive branch\n", - "Xc=1/(2*math.pi*fr*C) #ohm, capacitance reactance\n", - "Ic=V/Xc #A, current in capacitive branch \n", - "Zp=L/(R*C) #ohm , series impedance\n", - "I=V/Zp #A, line current\n", - "\n", - "#Result\n", - "print \"fr= \",round(fr/10**3,0),\"khz\"\n", - "print \"Il= \",Il,\"A\"\n", - "print \"Ic= \",Ic,\"A\"\n", - "print \"Zp= \",Zp,\"ohm\"\n", - "print \"I= \",I/10**(-3),\"mA\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "fr= 1592.0 khz\n", - "Il= 0.1 A\n", - "Ic= 0.1 A\n", - "Zp= 100000.0 ohm\n", - "I= 1.0 mA\n" - ] - } - ], - "prompt_number": 4 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 11.3 Page no. 379" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "import math\n", - "C=100*10**(-12) #F, capacitance\n", - "L=150*10**(-6) #H, inductance\n", - "R=15 #Ohms, resistance\n", - "\n", - "#Calculation\n", - "fr=1/(2*math.pi*math.sqrt(L*C))\n", - "Zp=L/(R*C)\n", - "Q=2*math.pi*fr*L/R\n", - "df=fr/Q #Bandwidth\n", - "\n", - "#The Result\n", - "print \" Impedance, Zp= \",Zp/10**3,\"kohm\"\n", - "print \" Quality Factor, Q= \",round(Q,1)\n", - "print \" Bandwidth, df= \",round(df/10**3,2),\"khz\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " Impedance, Zp= 100.0 kohm\n", - " Quality Factor, Q= 81.6\n", - " Bandwidth, df= 15.92 khz\n" - ] - } - ], - "prompt_number": 5 - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch12.ipynb b/Basic_Electronics_and_Linear_Circuits/ch12.ipynb deleted file mode 100755 index 5b2933a1..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch12.ipynb +++ /dev/null @@ -1,208 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:1fc7b4e7810aaec71230ef3ddc13645d6efc0b44874bc6bf484268f68693d914" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 12:Feedback in amplifiers" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 12.1 Page no.395" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "A=100.0 #Internal Gain\n", - "B=0.1 #Feedback Factor\n", - "\n", - "#Calculation\n", - "Af=A/(1+A*B) # Gain of Feedback Amplifier \n", - "# Result\n", - "print \" The Value of the Gain of Feedback Amplifier is = \",round(Af,2)" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Value of the Gain of Feedback Amplifier is, = 9.09\n" - ] - } - ], - "prompt_number": 1 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 12.2 Page no. 395" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Af=100.0 #Voltage Gain\n", - "Vin=.05 #V , Input Signal without Feedaback Gain\n", - "Vi=0.6 #V , Input Signal with Feedaback Gain\n", - "\n", - "#Calculation\n", - "Vo=Af*Vi\n", - "A=Vo/Vin\n", - "B=((A/Af)-1)/A\n", - "#Result\n", - "print \"The Value of the Internal Gain A is, A = \",A\n", - "print \" The Value of the Feedback Gain B is, B = percent \",round(B*100,2)" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "The Value of the Internal Gain A is, A = 1200.0\n", - " The Value of the Feedback Gain B is, B = percent 0.92\n" - ] - } - ], - "prompt_number": 2 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 12.3 Page no. 401" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "A=1000 #60dB Voltage Gain\n", - "B=0.005 #Negative Feedback\n", - "dAbyA=-0.12 #dA/A = 12 %\n", - "\n", - "#Calculation\n", - "dAfbyAf=1/(1+A*B)*dAbyA #dAf/Af=1/(1+A*B)*dA/A\n", - "\n", - "# Result\n", - "print \" The change in overall Gain of the Feedback Amplifier is\",dAfbyAf\n", - "print \"Therefore the overall gain of feedback amplifier will be reduce by \",-dAfbyAf*100,\"%\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The change in overall Gain of the Feedback Amplifier is -0.02\n", - "Therefore the overall gain of feedback amplifier will be reduce by 2.0 %\n" - ] - } - ], - "prompt_number": 3 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 12.4 Page no. 401" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Zi=1000.0 #Ohms\n", - "A=1000.0 #Voltage Gain\n", - "B=0.01 #Negative Feedback\n", - "\n", - "#Calculation\n", - "Zid=(1+A*B)*Zi\n", - "# Result\n", - "print \" The Value of the Input Impedance of the Feedback Amplifier is, Zid = \",Zid/10**3,\"K ohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Value of the Input Impedance of the Feedback Amplifier is, Zid = 11.0 K ohm\n" - ] - } - ], - "prompt_number": 4 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 12.5 Page no. 401" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "A=1000.0 #60dB, Voltage Gain\n", - "Zo=12000.0 #Ohms\n", - "Zod=600.0 #Ohms\n", - "dAbyA=0.1 #dA/A = 10 %\n", - "\n", - "#Calculation\n", - "B=((Zo/Zod)-1)/A #Zod=Zo/(1+A*B)\n", - "dAfbyAf=1/(1+A*B)*dAbyA #dAf/Af=1/(1+A*B)*dA/A\n", - "# Result\n", - "print \" The Feedback Factor of the Feedback Amplifier is, B = \",B*100,\"percent\"\n", - "print \" The change in overall Gain of the Feedback Amplifier is, dAf/Af = \",dAfbyAf*100,\"percent\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Feedback Factor of the Feedback Amplifier is, B = 1.9 percent\n", - " The change in overall Gain of the Feedback Amplifier is, dAf/Af = 0.5 percent\n" - ] - } - ], - "prompt_number": 6 - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch13.ipynb b/Basic_Electronics_and_Linear_Circuits/ch13.ipynb deleted file mode 100755 index 47cf6410..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch13.ipynb +++ /dev/null @@ -1,104 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:599e62479fb81312d9e71ded8b631cb3f6c046aff5ae2a1f3f8129c2f46ca250" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 13:Oscillators" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 13.1 Page no.421" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "L=58.6*10**(-6) # H, inductance\n", - "C=300*10**(-12) # F, capacitance\n", - "\n", - "#Calculation\n", - "import math\n", - "fo=1/(2*math.pi*math.sqrt(L*C))\n", - "\n", - "#Result\n", - "print \" The Frequency of Oscillation of Tuned Collector Oscillator is fo = \",round(fo/10**3,2),\"KHz\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 13.2 Page no.427" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "R=100000.0 # Ohms, resistance\n", - "C=0.01*10**(-6) #F, capacitance\n", - "\n", - "#Calculation\n", - "import math\n", - "fo=1/(2*math.pi*R*C*math.sqrt(6))\n", - "#Result\n", - "print \"The Frequency of Oscillation of Vacuum Tube Phase Shift Oscillator is fo = \",round(fo,2),\"Hz\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 13.3 Page no.427" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "R1=220000.0 # Ohms, Resistance 1\n", - "R2=220000.0 # Ohms Resistance 2\n", - "C1=250*10**(-12) #F, capacitance 1 \n", - "C2=250*10**(-12) #F, capacitance 2\n", - "\n", - "#Calculation\n", - "import math\n", - "fo=1/(2*math.pi*math.sqrt(R1*C1*R2*C2))\n", - "# Result\n", - "print \"The Frequency of Oscillation of Wein Bridge Oscillator is fo = \",round(fo/10**3,2),\"KHz\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch14.ipynb b/Basic_Electronics_and_Linear_Circuits/ch14.ipynb deleted file mode 100755 index f2764770..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch14.ipynb +++ /dev/null @@ -1,284 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:cfa443285df31619aefbaacada3721c633441a1550bfa091bb356c1fe13c7815" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 14 :Electronic Instruments" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 14.1 Page no.443" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Rm=100.0 #Ohms, coil resistance\n", - "Is=100*10**(-6 ) #A current sensivity\n", - "Vr=100.0 #V, voltage\n", - "\n", - "#Calculation\n", - "Rtotal=Vr/Is #series resistance\n", - "Rs=Rtotal-Rm #additional series resistance\n", - "#Result\n", - "print \" The Series Resistance to Convert given dArsonval movement into a Voltmeter is, Rs = \",Rs/10**3,\"Kohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Series Resistance to Convert given dArsonval movement into a Voltmeter is, Rs = 999.9 Kohm\n" - ] - } - ], - "prompt_number": 1 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 14.2 Page no. 445" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Rm=100.0 #. meter resistance #Ohms\n", - "CS=100*10**(-6) #A. current sensivity\n", - "Imax=10*10**(-3) #A. maximum current\n", - "\n", - "#Calculation\n", - "Ish=Imax-CS\n", - "Rsh=Rm*CS/Ish\n", - "# Result\n", - "print \" The Value of Shunt Resistance is, Rsh = \",round(Rsh,6),\"ohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Value of Shunt Resistance is, Rsh = 1.010101 ohm\n" - ] - } - ], - "prompt_number": 2 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 14.3 Page no.446" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "CS=100*10**(-6) #A, current source\n", - "R=100.0 #Ohms, resistance\n", - "Rm=900.0 #Ohms, resistance of a meter\n", - "\n", - "#(a)\n", - "#Calculation\n", - "Imax1=1*10**(-3) #A, maximum current\n", - "Rsh=CS*R/(Imax1-CS) #ohm, shunt path resistance\n", - "Rm1=Rm #ohm, meter branch resistance\n", - "Ish1=Imax1-CS #A shunt path current\n", - "Rsh1=Rm1*CS/Ish1 #ohm shunt path resistance\n", - "\n", - "#(b)\n", - "#Calculation\n", - "Imax2=0.01 #A, maximum current\n", - "Ish2=Imax2-CS #A, shunt path current\n", - "R1=(R*Ish2-Rm*CS)/(Ish2+CS) #ohm, resistance in branch 1\n", - "\n", - "#(c)\n", - "#Calculation\n", - "Imax3=100*10**(-3) #A. maximum current\n", - "Ish3=Imax3-CS #A, shunt path current\n", - "R2=((R-R1)*Ish3-Rm*CS)/(Ish3-CS) #ohm, resistance in branch 2\n", - "\n", - "#(d)\n", - "#Calculation\n", - "Imax4=500*10**(-3) #A , maximum current\n", - "Ish4=Imax4-CS #A, shunt path current\n", - "R3=((R-R1-R2)*Ish4-Rm*CS)/(Ish4-CS) #ohm, resistance in branch 3\n", - "\n", - "#(e)\n", - "#Calculation\n", - "Imax5=1 #A\n", - "Ish5=Imax5-CS #A, shunt path current\n", - "R4=((R-R1-R2-R3)*Ish5-Rm*CS)/(Ish5-CS) #ohm, resistance in branch 4\n", - "R5=R-R1-R2-R3-R4 #ohm, resistance in branch 2\n", - "\n", - "# Result\n", - "print \" Shunt Resistance =\",round(Rsh,6),\"ohm\"\n", - "print \" For Range switch at 1 mA , Rsh1 \",Rsh1,\"ohm\"\n", - "print \" For Range switch at 10 mA , R1 = \",R1,\"ohm\"\n", - "print \" For Range switch at 100 mA, R2 = \",round(R2,0),\"ohm\"\n", - "print \" For Range switch at 500 mA, R3 = \",round(R3,1),\"ohm\"\n", - "print \" For Range switch at 1 A , R4 = \",round(R4,1),\"ohm\"\n", - "print \" R5 = \",round(R5,1),\"ohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " Shunt Resistance = 11.111111 ohm\n", - " For Range switch at 1 mA , Rsh1 100.0 ohm\n", - " For Range switch at 10 mA , R1 = 90.0 ohm\n", - " For Range switch at 100 mA, R2 = 9.0 ohm\n", - " For Range switch at 500 mA, R3 = 0.7 ohm\n", - " For Range switch at 1 A , R4 = 0.1 ohm\n", - " R5 = 0.1 ohm\n" - ] - } - ], - "prompt_number": 3 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 14.4 Page no.469" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "DS=5 #V/cm, Deflection Sensitivity\n", - "l=10 #cm, Trace Length\n", - "\n", - "#Calculation\n", - "import math\n", - "Vp=DS*l\n", - "Vm=Vp/2\n", - "V=Vm/math.sqrt(2)\n", - "# Result\n", - "print \" The RMS AC Voltage is=\",round(V,3),\"V\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The RMS AC Voltage is= 17.678 V\n" - ] - } - ], - "prompt_number": 6 - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%pylab inline" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\n", - "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n", - "For more information, type 'help(pylab)'.\n" - ] - } - ], - "prompt_number": 1 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 14.5 Page no. 471" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "import numpy\n", - "#Given Circuit Data\n", - "Am=3.5 #V, Amplitude\n", - "tb=0.1*10**(-3) #seconds\n", - "TP=4 #Time Period\n", - "x=linspace(-10,10,1000)\n", - "plt.grid()\n", - "plot(x,cos(x))\n", - "title('Display of a sine wave voltage on CRO ')\n", - "show()\n", - "#Calculation\n", - "import math\n", - "Vm=2*Am\n", - "V=Vm/math.sqrt(2)\n", - "T=TP*tb\n", - "f=1/T\n", - "\n", - "# Result\n", - "print \"The Magnitude of Wave Voltage, \",round(V,2),\"V\"\n", - "print \" The Frequency of Wave Voltage, f = \",f/10**3,\"KHz\"\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAEICAYAAACzliQjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwUWfw+FwNAQXfQ6Hw9EQXPQ5HA5HQ/x/swF7YoxaJw4AAAAASUVORK5CYII=\n" - }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "The Magnitude of Wave Voltage, 4.95 V\n", - " The Frequency of Wave Voltage, f = 2.5 KHz\n" - ] - } - ], - "prompt_number": 2 - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch2.ipynb b/Basic_Electronics_and_Linear_Circuits/ch2.ipynb deleted file mode 100755 index 56897172..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch2.ipynb +++ /dev/null @@ -1,144 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:d04dc734c5bc464767e0da96b38331e03b832b88f0bd8644b242b3682feeb9d9" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 2:Current and Voltage Source" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 2.1 Page no.39" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vs=2 #V open circuit voltage\n", - "Rs=1 #ohm . internal impedence\n", - "#Current Source or Norton's Representaion (Parallel Current Source & Resistor\n", - "Is=Vs/Rs #Ampere, short circuit current\n", - "#result\n", - "print \"The Short Circuit Current Value is \",Is,\"A\"\n", - "print \"The Source Impedence Value is \",Rs,\"ohm\"\n", - "print \"The Current Source & Source Impedance are connected in Parallel.\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 2.2 Page no.40" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Is=0.2 #Amperes\n", - "Zs=100 #Ohms\n", - "#Voltage Source or Thevenin's Representaion (Series Voltage Source & Resistor)\n", - "Vs=Is*Zs #Volts\n", - "# Results \n", - "print \"The Open Circuit Voltage is \",Vs,\"V\"\n", - "print \"The Source Impedence Value is \",Zs,\"ohm\"\n", - "print \"The Voltage Source & Source Impedance are connected in Series.\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 2.3 Page no.40" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Is=1.5*10**(-3) #Amperes ,source current\n", - "Zs=2000 #Ohms, resistance connected to the loads\n", - "Z1=10000 #Ohms , load resistance 1\n", - "Z2=40000 #Ohms load resistance 2\n", - "#Calculation for Current Source Representation\n", - "Zl=Z1*Z2/(Z1+Z2)\n", - "I2=Is*Zs/(Zs+Zl)\n", - "I4I=I2*Z1/(Z1+Z2) #Using Current Divider Rule\n", - "\n", - "#Calculation for Current Source Representation\n", - "Vs=Is*Zs #Open Circuit Volatge\n", - "I=Vs/(Zs+Zl)\n", - "I4V=I*Z1/(Z1+Z2) #Using Current Divider Rule\n", - "# Results \n", - "print \"The Load Current using Current Source Representaion is I4I = \",I4I,\"A\"\n", - "print \"The Load Current using Voltage Source Representaion is I4V = \",I4V,\"A\"\n", - "print \"I4I==I4V so\"\n", - "print \" Both Results are same.\"\n", - "\n" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 2.4 Page no.45" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - " \n", - "Vs=0.01 #V ,dc voltage\n", - "Rs=1000 # ohm, resistance\n", - "#Output Side resistance\n", - "Ro1=20000 #ohm, 20 kOhms\n", - "Ro2=2000 # Ohms\n", - "\n", - "#Calculation\n", - "i=Vs/Rs #Input Current\n", - "Io=100*i #Output Current\n", - "Il=Io*Ro1/(Ro1+Ro2) #Using Current Divider Rule\n", - "Vo=Il*Ro2 #Output Volatge\n", - "\n", - "# Result\n", - "print \"The Output Voltage Vo = \",round(Vo,3),\"V\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch4.ipynb b/Basic_Electronics_and_Linear_Circuits/ch4.ipynb deleted file mode 100755 index 701f4aaf..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch4.ipynb +++ /dev/null @@ -1,188 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:ae9612ced78590c195456849014e70cbd1cdee113840d747c19ee249579f79a3" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 4:Semiconductor Diode" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 4.1 Page No.85" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vrms=220 #Volts, power supply\n", - "n2=1 #Assumption\n", - "n1=12*n2 #Turns Ratio\n", - "\n", - "#Calculation\n", - "import math\n", - "Vp=math.sqrt(2)*Vrms #Maximum(Peak) Primary Voltage\n", - "Vm=n2*Vp/n1 #Maximum Secondary Voltage\n", - "Vdc=Vm/math.pi #DC load Voltage \n", - "# Results \n", - "print \"The DC load Voltage is = \",round(Vdc,2),\"V\"\n", - "print \"The Peak Inverse Voltage(PIV) is = \",round(Vm,1),\"V\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 4.2 Page No.90" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vrms=220 #Volts, power supply rms voltage\n", - "n2=1 #Assumption\n", - "n1=12*n2 #Turns Ratio\n", - "\n", - "#Calculation\n", - "import math\n", - "Vp=math.sqrt(2)*Vrms #Maximum(Peak Primary Voltage\n", - "Vm=n2*Vp/n1 #Maximum Secondary Voltage\n", - "Vdc=2*Vm/math.pi #DC load Voltage \n", - "\n", - "# Results \n", - "print \"The DC load Voltage is = \",round(Vdc,1),\"V\"\n", - "print \"The Peak Inverse Voltage(PIV of Bridge Rectifier is = \",round(Vm,1),\"V\"\n", - "print \"The Peak Inverse Voltage(PIV of Centre-tap Rectifier is = \",round(2*Vm,1),\"v\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 4.3 Page No.95" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "import math\n", - "Rl=1000.0 #Ohms, load resistance\n", - "rd=10.0 #Ohms forward base dynamic resistance\n", - "Vm=220.0 #Volts(Peak Value of Voltage)\n", - "#Calculation\n", - "Im=Vm/(rd+Rl) #Peak Value of Current\n", - "\n", - "# Result\n", - "print \"The Peak Value of Current is = \",round(Im*1000,1),\"mA\"\n", - "\n", - "#(b) dc or av value of current\n", - "\n", - "Idc=2*Im/math.pi #DC Value of Current\n", - "# Results \n", - "print \"The DC or Average Value of Current is \",round(Idc*1000,2),\"mA\"\n", - "\n", - "#(c)\n", - "Irms=Im/math.sqrt(2) #RMS Value of Current\n", - "# Results \n", - "print \"The RMS Value of Current is = \",round(Irms*1000,1),\"mA\"\n", - "\n", - "#(d)\n", - "r=math.sqrt((Irms/Idc)**2-1) #Ripple Factor\n", - "# Results i\n", - "print \" The Ripple Factor r = \",round(r,3)\n", - "\n", - "#(e)\n", - "Pdc=Idc**2*Rl\n", - "Pac=Irms**2*(rd+Rl)\n", - "n=Pdc/Pac #Rectification Efficiency\n", - "# Results\n", - "print \"The Rectification EFficiency n(eeta) = percent.\",round(n*100,2)" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 4.4 Page No.103" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vz=9.1 #Volts\n", - "P=0.364 #Watts\n", - "#Calculation\n", - "Iz=P/Vz\n", - "#Result\n", - "print \" The Maximum permissible Current is \",Iz*1000,\"mA\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 4.5 Page No.105" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Ci=18*10**(-12) #i.e. 18 pF, capacitance of diode\n", - "Vi=4 #volt, initial voltage\n", - "Vf=8 #v, final voltage\n", - "\n", - "#Calculation\n", - "import math\n", - "Vf=8 \n", - "K=Ci*math.sqrt(Vi)\n", - "Cf=K/math.sqrt(Vf)\n", - "#Result\n", - "print \" The Final Value of Capacitance is C = \",round(Cf/10**(-12),3),\"pF\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch5.ipynb b/Basic_Electronics_and_Linear_Circuits/ch5.ipynb deleted file mode 100755 index 89258a51..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch5.ipynb +++ /dev/null @@ -1,385 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:fb72fb6e3e7bfcc92ab695858992d86597c1a24269bab39240e9f25a8dff8c2d" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 5: Transistors" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 5.1 Page No 134" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "alpha=0.98 #alpha(dc), current gain\n", - "Ico=1*10**(-6) #Ampere, collector leakage current\n", - "Ie=1*10**(-3) # Ampere, emitter current\n", - "\n", - "#Calculation\n", - "Ic=alpha*Ie+Ico #Collector Current\n", - "Ib=Ie-Ic #Base Current \n", - "#result\n", - "print \" The Collector Current is Ic= \",Ic*1000,\"mA\"\n", - "print \" The Base Current is Ib= \",Ib*10**6,\"microA\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Collector Current is Ic= 0.981 mA\n", - " The Base Current is Ib= 19.0 microA\n" - ] - } - ], - "prompt_number": 1 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 5.2 Page No 141" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "dIe=(0.7-0.3)*10**(-3) #A, change in emitter current\n", - "dVeb=(0.7-0.62) #V, change in emitter base voltage\n", - "#Calculation\n", - "ri=dVeb/dIe #Dynamic Input Resistance at Vcb= -10 V \n", - "#Result\n", - "print \" The Dynamic Input Resistance is ri= \",ri,\"ohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Dynamic Input Resistance is ri= 200.0 ohm\n" - ] - } - ], - "prompt_number": 7 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 5.3 Page No 144" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "dIe=1*10**(-3) #A, change in emitter current\n", - "dIc=0.99*10**(-3) #A, change in the collector current\n", - "\n", - "#Calculation\n", - "hfb=dIc/dIe #Short Circuit Current Gain\n", - "#Result\n", - "print \"The Short Circuit Current Gain is alpha or hfb= \",hfb" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 5.4 Page No 147 " - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "dIe=1*10**(-3) #A, change in emitter current\n", - "dIc=0.995*10**(-3) #A, change in collector current\n", - "\n", - "#Calculation\n", - "alpha=dIc/dIe #Common Base Short Circuit Current Gain\n", - "#Result\n", - "print \" The Common Base Short Circuit Current Gain is alpha= \",alpha\n", - "\n", - "#(b)\n", - "beeta=alpha/(1-alpha) #Common Emitter Short Circuit Current Gain\n", - "# Result\n", - "print \" The Common Emitter Short Circuit Current Gain is beeta= \",beeta\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Common Base Short Circuit Current Gain is alpha= 0.995\n", - " The Common Emitter Short Circuit Current Gain is beeta= 199.0\n" - ] - } - ], - "prompt_number": 6 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 5.5 Page No 147 " - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Beeta=100.0 #dc current gain\n", - "\n", - "#Calculation\n", - "Alpha=Beeta/(Beeta+1) #DC Current Gain in Common Base Configuration\n", - "# Result\n", - "print \" The DC Current Gain in Common Base Configuration is Alpha= \",round(Alpha,2)" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The DC Current Gain in Common Base Configuration is Alpha= 0.99\n" - ] - } - ], - "prompt_number": 5 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 5.6 Page No 150" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vce=10 #V, collector emitter voltage\n", - "Ib=30*10**(-6) #A, base current\n", - "\n", - "#Calculation from Given Output Characteristics at Ib = 30uA\n", - "dVce=(12.5-7.5) #V, change in collector emitter voltage\n", - "dic=(3.7-3.5)*10**(-3) #A, change in collector current\n", - "Ic=3.6*10**(-3) #A, collector current at operating point \n", - "ro=dVce/dic # Dynamic Output Resistance\n", - "Beeta_dc=Ic/Ib # DC Current Gain\n", - "Beeta_ac=((4.7-3.6)*10**(-3))/((40-30)*10**(-6)) #AC Current Gain, From Graph, Bac=delta(ic)/delta(ib) for given Vce\n", - "\n", - "# Result\n", - "print \"Dynamic Output Resistance ,ro = \",ro/10**(3),\"kohm\"\n", - "print \" DC Current Gain ,Bdc = \",Beeta_dc\n", - "print \" AC Current Gain ,Bac = \",Beeta_ac" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "Dynamic Output Resistance ,ro = 25.0 kohm\n", - " DC Current Gain ,Bdc = 120.0\n", - " AC Current Gain ,Bac = 110.0\n" - ] - } - ], - "prompt_number": 4 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 5.7 Page No 159" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - " \n", - "Vcc=12 #V, collector bias juncyion voltage\n", - "Rc=1000.0 #Ohms, collector resistance\n", - "Vbb=10.7 #V. base bias junction voltage\n", - "Rb=200000.0 #Ohms, base resistance\n", - "Vbe=0.7 #V, base emitter voltage\n", - "\n", - "#Calculation\n", - "Ib=(Vbb-Vbe)/Rb # base current\n", - "#Value of Ib comes out to be 50uA. A dotted Curve is drawn for \n", - "#Ib=40uA and Ib=60uA. At the Point of Intersection:\n", - "Vce=6 #V, collector emitter voltage\n", - "Ic=6*10**(-3) #A, collector current\n", - "# Result\n", - "print \" Q point: Ib = \",Ib/10**(-6),\"microA\"\n", - "print \" Vce = \",Vce,\"V\"\n", - "print \" Ic = \",Ic/10**(-3),\"mA\"\n", - "#Plot\n", - "\n", - "#DC Load LIne AT Ib=50 microA\n", - "Vce1=[0,12]\n", - "Ic1=[12,0]\n", - "a1=plot(Vce1,Ic1)\n", - "xlim(0,14)\n", - "ylim(0,17)\n", - "\n", - "\n", - "# AT Ib=20 microA\n", - "Vce2=[0,1,12]\n", - "Ic2=[0,1.5,3]\n", - "a2=plot(Vce2,Ic2)\n", - "\n", - "# AT Ib=40 microA\n", - "Vce3=[0,1,12]\n", - "Ic3=[0,4,5]\n", - "a3=plot(Vce3,Ic3)\n", - "\n", - "#At IB=50\n", - "Vcex=[3.2,9]\n", - "Icx=[5.5,6]\n", - "ax=plot(Vcex,Icx,linestyle='--')\n", - "qx=plot(6.1,5.9,marker='o',label='$Q point$')\n", - "legend()\n", - "\n", - "# AT Ib=60 microA\n", - "Vce4=[0,1,12]\n", - "Ic4=[0,6.5,8]\n", - "a4=plot(Vce4,Ic4)\n", - "\n", - "# AT Ib=80 microA\n", - "Vce5=[0,1,12]\n", - "Ic5=[0,9,10]\n", - "a5=plot(Vce5,Ic5)\n", - "\n", - "# AT Ib=100 microA\n", - "Vce6=[0,1,12]\n", - "Ic6=[0,12,12.5]\n", - "a6=plot(Vce6,Ic6)\n", - "\n", - "# AT Ib=120 microA\n", - "Vce7=[0,1,12]\n", - "Ic7=[0,14.2,15]\n", - "a7=plot(Vce7,Ic7)\n", - "xlabel(\"$Vce(volt)$\")\n", - "ylabel(\"$Ic(mA)$\")\n", - "show(a1)\n", - "show(ax)\n", - "show(qx)\n", - "show(a2)\n", - "show(a3)\n", - "show(a4)\n", - "show(a5)\n", - "show(a6)\n", - "show(a7)\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " Q point: Ib = 50.0 microA\n", - " Vce = 6 V\n", - " Ic = 6.0 mA\n" - ] - }, - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAYYAAAEOCAYAAACNY7BQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nI4lBCCGEGUkMQgghzPx/TjiQ+AqbBlQAAAAASUVORK5CYII=\n" - } - ], - "prompt_number": 15 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 5.8 Page No 173" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "u=80.0 # Amplification Factor\n", - "gm=200*10**(-6) # S, Transconductance\n", - "\n", - "#Calculation\n", - "rd=u/gm #Dynamic Drain Resistance\n", - "# Result\n", - "print \" The Dynamic Drain Resistance of JFET is rd= \",rd/10**(3),\"kohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Dynamic Drain Resistance of JFET is rd= 400.0 kohm\n" - ] - } - ], - "prompt_number": 3 - }, - { - "cell_type": "code", - "collapsed": false, - "input": [], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch6.ipynb b/Basic_Electronics_and_Linear_Circuits/ch6.ipynb deleted file mode 100755 index abbcf8b9..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch6.ipynb +++ /dev/null @@ -1,197 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:e45efbc918d6e082147a3abf5687f38acaf875f9fd899adb5638679d888fbdcb" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 6: Vaccum Tubes" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 6.1 Page no.195" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "\n", - "from pylab import *\n", - "#Given Circuit Data\n", - "V=[0,0.5,1,1.5,2] #V, voltage\n", - "I=[0,1.6,4,6.7,9.4] #mA, current\n", - "\n", - "#Calculation\n", - "dVp=0.5 #V, change in plate voltage\n", - "dIp=2.7*10**(-3) #A, change in plate current\n", - "rp=dVp/dIp # Dynamic Plate Resistance\n", - "\n", - "#Result\n", - "print \"The Dynamic Plate Resistance is rp= \",rp,\"ohm\"\n", - "\n", - "#plot\n", - "\n", - "a=plot(V,I)\n", - "xlabel(\"V\") \n", - "ylabel(\"I (mA)\") \n", - "\n", - "show(a)\n", - "\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "The Dynamic Plate Resistance is rp= 185.185185185 ohm\n" - ] - }, - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEKCAYAAAAfGVI8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nb3wzYgAAAABJRU5ErkJggg==\n" - } - ], - "prompt_number": 3 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 6.2 Page no.202" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "from math import *\n", - "from pylab import *\n", - "#Calculation\n", - "dip=(14.0-10.7)*10**(-3) #A\n", - "dvp=20 #V\n", - "rp=dvp/dip\n", - "diP=(12.4-5.3)*10**(-3) #A\n", - "dvG=1 #V\n", - "gm=diP/dvG\n", - "u=gm*rp\n", - "ut=(192-150)/1\n", - "\n", - "# Result\n", - "print \" The Plate AC Resistance is rp= \",round(rp/10**(3),2),\"kohm\"\n", - "print \" The Mutual Conductance is gm= \",gm/10**(-3),\"mS\"\n", - "print \" The Graphical Amplification Factor is u= \",round(u,2)\n", - "print \" The Theoretical Amplification Factor is ut= \",ut\n", - "\n", - "\n", - "#plot\n", - "#At Vg=0\n", - "V1=[0,50,100,150]\n", - "I1=[0,3.5,11.2,20.0]\n", - "\n", - "#at Vg=-1\n", - "V2=[60,100,150,200]\n", - "I2=[0,4,12.4,21.5]\n", - "\n", - "\n", - "#at Vg=-2\n", - "V3=[100,150,200]\n", - "I3=[0,5.4,14.1]\n", - "\n", - "#at Vg=-3\n", - "V4=[160,200,250]\n", - "I4=[0,3.4,12.4]\n", - "\n", - "#at Vg=-4\n", - "V5=[220,250,300]\n", - "I5=[0,2.5,11.3]\n", - "\n", - "figure(1)\n", - "import numpy \n", - "import pylab\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(111)\n", - "\n", - "\n", - "a1=plot(V1,I1)\n", - "a2=plot(V2,I2)\n", - "a3=plot(V3,I3)\n", - "a4=plot(V4,I3)\n", - "a5=plot(V5,I4)\n", - "xlabel(\"Vp (V)\") \n", - "ylabel(\"Ip(mA)\") \n", - "ax.annotate('vg=0', xy=(152,21),\n", - " arrowprops=dict(facecolor='black', shrink=0.5),\n", - " )\n", - "ax.annotate('vg=-1', xy=(200,21.5), \n", - " arrowprops=dict(facecolor='black', shrink=0.5),\n", - " )\n", - "ax.annotate('vg=-2', xy=(200,14.1), \n", - " arrowprops=dict(facecolor='black', shrink=0.5),\n", - " )\n", - "ax.annotate('vg=-3', xy=(250,12.4),\n", - " arrowprops=dict(facecolor='black', shrink=0.5),\n", - " )\n", - "ax.annotate('vg=-4',xy=(300,11.3), \n", - " arrowprops=dict(facecolor='black', shrink=0.5),\n", - " )\n", - "show(a1)\n", - "show(a2)\n", - "show(a3)\n", - "show(a4)\n", - "show(a5)\n", - "\n", - "\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Plate AC Resistance is rp= 6.06 kohm\n", - " The Mutual Conductance is gm= 7.1 mS\n", - " The Graphical Amplification Factor is u= 43.03\n", - " The Theoretical Amplification Factor is ut= 42\n" - ] - }, - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAZkAAAEMCAYAAAAWDss+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n" - } - ], - "prompt_number": 30 - }, - { - "cell_type": "code", - "collapsed": false, - "input": [], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch7.ipynb b/Basic_Electronics_and_Linear_Circuits/ch7.ipynb deleted file mode 100755 index 7a081d42..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch7.ipynb +++ /dev/null @@ -1,610 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:a8e6eec0c3406a8b34f53cdcd04f5f3e158306e880eeefff72f3f3980fec597f" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 7 :Transistor Biasing And Stabilization of Operation Point" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.1 Page No.230" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=9.0 #V, collector bias junction voltage\n", - "Rb=300*10**3 #Ohms, , base resistance\n", - "Rc=2*10**3 #Ohms, collector resistance\n", - "Beeta=50.0 #current gain factor\n", - "\n", - "#Calculation\n", - "Ib=(Vcc)/Rb\n", - "Ic=Beeta*Ib\n", - "Icsat=Vcc/Rc\n", - "Vce=Vcc-Ic*Rc\n", - "\n", - "#Result\n", - "print \"a) Base current is \",Ib,\"A\"\n", - "print \"b) collector current is = \",Ic/10**(-3),\"mA\"\n", - "print \"collector saturation current is = \",Icsat/10**(-3),\"mA\"\n", - "if Ic < Icsat:\n", - " \n", - " print\"Since Ic < Icsat \\nSo Transistor is not in saturation\" \n", - "else:\n", - " print \"Transistor is in saturation\"\n", - "\n", - "print \"c) The collector to emitter voltage is = \",Vce,\"V\"\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "a) Base current is 3e-05 A\n", - "b) collector current is = 1.5 mA\n", - "collector saturation current is = 4.5 mA\n", - "Since Ic < Icsat \n", - "So Transistor is not in saturation\n", - "c) The collector to emitter voltage is = 6.0 V\n" - ] - } - ], - "prompt_number": 21 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.2 Page No.230" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=10.0 #V, collector bias junction voltage\n", - "Rb=100*10**3 #Ohms, base resistance\n", - "Rc=1*10**3 #Ohms, collector resistance\n", - "Beeta=60 #current gain\n", - " \n", - "#Calculation\n", - "Ib=(Vcc)/Rb #A, base current\n", - "Ic=Beeta*Ib #A, collector current\n", - "Icsat=Vcc/Rc #A, collector saturated current\n", - "Vce=Vcc-Ic*Rc #V, collector emitter voltage\n", - "\n", - "#Result\n", - "print \"a) Base current is \",Ib*10**6,\"microA\"\n", - "print \"b) collector current is \",Ic*10**3,\"mA\"\n", - "print \"collector saturation current is \",Icsat*10**3,\"mA\"\n", - "if Ic < Icsat:\n", - " \n", - " print\"Since Ic < Icsat \\nSo Transistor is not in saturation\" \n", - "else:\n", - " print \"Transistor is in saturation\"\n", - "print \"c) The collector emitter voltage is \",Vce,\"V\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "a) Base current is 100.0 microA\n", - "b) collector current is 6.0 mA\n", - "collector saturation current is 10.0 mA\n", - "Since Ic < Icsat \n", - "So Transistor is not in saturation\n", - "c) The collector emitter voltage is 4.0 V\n" - ] - } - ], - "prompt_number": 23 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.3 Page No.231" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=10.0 #V, collector bias junction voltage\n", - "Rb=100*10**3 #Ohms, Base resistance\n", - "Rc=1*10**3 #Ohms, collector resistance\n", - "Beeta=150 #current gain\n", - "\n", - "#Calculation\n", - "Ib=(Vcc)/Rb #Base current\n", - "Ic=Beeta*Ib #collector resistance\n", - "Icsat=Vcc/Rc #A, collector saturation current\n", - "Vce=0 #V, collector emitter voltage\n", - "\n", - "#Result\n", - "print \"collector current is Ic = \",Ic/10**(-3),\"mA\"\n", - "print \"collector saturated current is \",Icsat*10**3,\"mA\" \n", - "if Ic < Icsat:\n", - " \n", - " print\" Transistor is not in saturation.\" \n", - "else:\n", - " print \"Since Ic > Icsat \\n So Transistor is in saturation\"\n", - "print \"collector emitter voltage is \",Vce,\"V\"\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "collector current is Ic = 15.0 mA\n", - "collector saturated current is 10.0 mA\n", - "Since Ic > Icsat \n", - " So Transistor is in saturation\n", - "collector emitter voltage is 0 V\n" - ] - } - ], - "prompt_number": 25 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.4 Page No.231" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=6 #V,collector base junction voltage\n", - "Vbe=0.3 #V,base emittor voltage\n", - "Icbo=.000002 #A,colector leakage current\n", - "Ic=.001 #A,collector current\n", - "Beeta=20.0\n", - "\n", - "#Calculation\n", - "#Case 1: Considering Icbo and Vbe in the calculations\n", - "Ib=(Ic-(Beeta+1)*Icbo)/Beeta\n", - "print Ib\n", - "Rb1=(Vcc-Vbe)/Ib\n", - "print \"value of base resistance is =\",round(Rb1/1000,3),\"K ohm\"\n", - "\n", - "#Case 2: Neglecting Icbo and Vbe in the calculations\n", - "Ib2=Ic/Beeta\n", - "Rb2=Vcc/Ib2\n", - "#Percentage Error\n", - "E=(Rb2-Rb1)/Rb1*100\n", - "#Displaying The Results in Command Window\n", - "print\"The Base Resistance (Neglecting Icbo and Vbe) is \",Rb2/1000,\"k ohm\"\n", - "print\" Percentage Error is = \",round(E,3)\n", - "\n", - "#b Due to rise in temprature\n", - "beeta1=25.0\n", - "Icbo1=10.0\n", - "Ic1=beeta1*Ib+(beeta1+1)*Icbo1*10**-6\n", - "print \"Now collector current is \",round(Ic1*10**3,2),\"mA\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "4.79e-05\n", - "value of base resistance is = 118.998 K ohm\n", - "The Base Resistance (Neglecting Icbo and Vbe) is 120.0 k ohm\n", - " Percentage Error is = 0.842\n", - "Now collector current is 1.46 mA\n" - ] - } - ], - "prompt_number": 40 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.5 Page No.235" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=10.0 #V,collectoe base junction voltage\n", - "Rc=500.0 #Ohms,colector resistance\n", - "Rb=500000 #Ohms,base resistance\n", - "Beeta=100.0 #current gain\n", - "#Calculation\n", - "Ib=Vcc/(Rb+Beeta*Rc) #emittor currenr\n", - "Ic=Beeta*Ib\n", - "Ie=Ic\n", - "Vce=Vcc-Ic*Rc\n", - "Vc=Vce\n", - "\n", - "# Results \n", - "print \"emittor current is \",round(Ie*1000,1),\"mA\"\n", - "print\"The collector voltage is \",round(Vc,1),\"V\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.6 Page No.235" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "#Given Circuit Data\n", - "Vcc=20.0 #V,collector base voltage\n", - "Rc=2000.0 #Ohms.collector resistance\n", - "Rb=200000.0 #Ohms,base resistance\n", - "Beeta1=50.0 #current gain factor\n", - "Beeta2=200.0\n", - "\n", - "#Calculation CASE-1: Minimum Collector Current\n", - "#from fig 7.14\n", - "Ibmin=Vcc/(Rb+Beeta1*Rc)\n", - "Icmin=Beeta1*Ibmin\n", - "#result\n", - "print \"minimum base curent is \",round(Ibmin,6),\"A\"\n", - "print \"minimum collector current is \",round(Icmin*1000,3),\"mA\"\n", - "#Calculation CASE-2: Maximum Collector Current\n", - "Ibmax=Vcc/(Rb+Beeta2*Rc)\n", - "Icmax=Beeta2*Ibmax\n", - "\n", - "#Results \n", - "print\"The maximum base current = \",round(Ibmax/10**(-3),6),\"A\"\n", - "print\"The Maximum Collector Current = \",round(Icmax/10**(-3),2),\"mA\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.7 Page No.238" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=10.0 #V collector junction voltage\n", - "Rc=2000.0 #Ohms collector resistane\n", - "Rb=1000000.0 #Ohms,base resistance\n", - "Re=1000.0 #Ohms emittor resstance\n", - "Beeta=100.0 #current gain\n", - "\n", - "#Calculation\n", - "Ib=Vcc/(Rb+(Beeta+1)*Re)\n", - "Ic=Beeta*Ib\n", - "Ie=Ic+Ib\n", - "#Results \n", - "print \" The Collector Current Ic = \",round(Ic*1000,3),\"mA\"\n", - "print \" The Base Current Ib .\",round(Ib*1000000,2),\"microA\"\n", - "print \" The Emitter Current Ie = \",round(Ie*1000,3),\"mA\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.8 Page No.239" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=6 #V,collector bias junction volage\n", - "Vbe=0.3 #V base emittor voltage\n", - "Rc=50 #Ohms collector resistance\n", - "Rb=10*10**3 #Ohms base resistance\n", - "Re=100 #Ohms emittor resistance\n", - "Beeta1=50 # gain factor\n", - "Beeta2=200\n", - "\n", - "#Calculation CASE-1: Minimum Emitter Current & corresponding Vce\n", - "Iemin=(Vcc-Vbe)*(Beeta1+1)/(Rb+(Beeta1+1)*Re)\n", - "Vcemin=Vcc-(Rc+Re)*Iemin\n", - "#Calculatioen CASE-2: Maximum Emitter Current & corresponding Vce\n", - "Iemax=(Vcc-Vbe)*(Beeta2+1)/(Rb+(Beeta2+1)*Re)\n", - "Vcemax=Vcc-(Rc+Re)*Iemax\n", - "\n", - "#Results \n", - "print\"The Minimum Emitter Current Ie(min) is\",round(Iemin*1000,2),\"mA\"\n", - "print \"The Corresponding Vce = V .\",round(Vcemin,1),\"v\"\n", - "print \"The Maximum Emitter Current Ie(max) = .\",round(Iemax*1000,1),\"mA\"\n", - "print \"The Corresponding Vce = V .\",round(Vcemax,1),\"v\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.9 Page No. 240" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=6.0 #V, collector bias junction voltage\n", - "Vbe=0.3 #V, base emitter voltage\n", - "Rc=1*10**3 #Ohms, collector resistance\n", - "Rb=10*10**3 #Ohms, base resistance\n", - "Re=100.0 #Ohms, emitter resistance\n", - "Beeta1=50 #current gain factor\n", - "Beeta2=200\n", - "Ie1=19.25*10**(-3) #A,for beeta=50, from example 7.8 \n", - "Ie2=38.2*10**(-3) #A,for beeta=200, from example 7.8\n", - "\n", - "#Calculation (i)\n", - "\n", - "Ie1=19.25*10**(-3) #A,for beeta=50, from example 7.8 \n", - "Vce=Vcc-(Rc+Re)*Ie1 #V, collector emitter voltage\n", - "Icsat1=Vcc/(Rc+Re) #collector saturated current\n", - "Vcesat1=0\n", - "print \"The collector voltage is Vcc \",Vcc,\"V\"\n", - "print \"The collector emitter voltage is Vce\",Vce,\"V\"\n", - "print \"Because Collector voltage is greater than collector emitter voltage so Transistor is in saturation \"\n", - "print \"collector saturated current is \",round(Icsat1*10**3,2),\"mA\"\n", - "print \"collector emitter satirated voltage is\",Vcesat1,\"V\"\n", - "\n", - "# ii\n", - "Icsat2=Icsat1\n", - "Vcesat2=Vcesat1\n", - "print \"(ii) collector saturated current is \",round(Icsat2*10**3,3),\"mA\"\n", - "print \"collector emitter satirated voltage is\",Vcesat2,\"V\"\n", - "\n", - "\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "The collector voltage is Vcc 6.0 V\n", - "The collector emitter voltage is Vce -15.175 V\n", - "Because Collector voltage is greater than collector emitter voltage so Transistor is in saturation \n", - "collector saturated current is 5.45 mA\n", - "collector emitter satirated voltage is 0 V\n", - "(ii) collector saturated current is 5.455 mA\n", - "collector emitter satirated voltage is 0 V\n" - ] - } - ], - "prompt_number": 48 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.10 Page No.240" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=9 #V,collector bias junction voltge\n", - "Vce=3 #V,collector emittor voltage\n", - "Re=500 #Ohms,emittor resistance\n", - "Ic=8*10**(-3) #A,collector current\n", - "Beeta=80\n", - "#Calculation\n", - "Ib=Ic/Beeta\n", - "Rb=(Vcc-(Beeta+1)*Ib*Re)/Ib\n", - "#Displaying The Results in Command Window\n", - "print\"The Base Resistance is :\",round(Rb/1000,5),\"kohm\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.11 Page No.242" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=12.0 #V collector bias junction voltage\n", - "Vbe=0.3 #V base emitter junction voltage\n", - "R1=40000.0 #Ohms resistance\n", - "R2=5000.0 #Ohms resistance\n", - "Re=1000.0 #Ohms emitter reistance\n", - "Rc=5000.0 #Ohms collector resistance\n", - "Beeta=60\n", - "\n", - "#Calculation\n", - "Vb=(R2/(R1+R2))*Vcc\n", - "Ve=Vb-Vbe\n", - "Ie=Ve/Re\n", - "Ic=Ie\n", - "Vc=Vcc-Ic*Rc\n", - "Vce=Vc-Ve\n", - "# Results \n", - "print\" V2= Vb \",round(Vb,1),\"v\"\n", - "print\" Ve = \",round(Ve,1),\"v\"\n", - "print\" Ie = \",round(Ie/10**(-3),1),\"mA\"\n", - "print\" Ic = \",round(Ic/10**(-3),1),\"mA\"\n", - "print\" Vc = \",round(Vc,0),\"v\"\n", - "print\" Vce = \",round(Vce,0),\"v\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.12 Page No.243" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=15.0 #V collector bias junction voltage\n", - "R1=200.0 #Ohms resistor 1\n", - "R2=100.0 #Ohms resistor 2\n", - "Rc=20.0 #Ohms collector resistace\n", - "Ic=.1 #A collector current\n", - "\n", - "#Calculation\n", - "Ie=Ic\n", - "Vb=(R2/(R1+R2))*Vcc\n", - "Ve=Vb # Neglecting Vbe\n", - "Re=Ve/Ie\n", - "Vce=Vcc-(Rc+Re)*Ic\n", - "# Results\n", - "print\" The Emitter Resistance is Re = .\",Re,\"ohm\"\n", - "print\" The Collector to Emitter Voltage is Vce = \",Vce,\"v\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.13 Page No.246" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=12.0 #V collector bias junction voltage\n", - "Vbe=0.3 #V base emitter voltage\n", - "R1=40000.0 #Ohms given resistance\n", - "R2=5000.0 #Ohms\n", - "Re=1000.9 #Ohms emitter resistance\n", - "Rc=5000.0 #Ohms collector resistance\n", - "Beeta=60\n", - "#Calculation\n", - "Vth=(R2/(R1+R2))*Vcc\n", - "Rth=R1*R2/(R1+R2)\n", - "Ib=(Vth-Vbe)/(Rth+Beeta*Re)\n", - "Ic=Beeta*Ib\n", - "Vce=Vcc-Ic*(Rc+Re)\n", - "\n", - "# Results \n", - "print \"collector current is \",round(Ic*1000,2),\"mA\"\n", - "print \"collector to emitter voltage = \",round(Vce,2),\"v\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 7.14 Page No.248" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=12 #V collector bias junction voltage\n", - "Vee=15.0 #V emittor bias junction voltage\n", - "Rc=5000.0 #Ohms collector resistance\n", - "Re=10000.0 #Ohms emitter resistance\n", - "Rb=10000.0 #Ohms base resistance\n", - "Beeta=100\n", - "\n", - "#Calculation\n", - "Ie=Vee/Re\n", - "Ic=Ie\n", - "Vce=Vcc-Ic*Rc\n", - "#Displaying The Results in Command Window\n", - "print\" Ic = \",Ic/10**(-3),\"mA\"\n", - "print\" Vce = \",Vce,\"v\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch8.ipynb b/Basic_Electronics_and_Linear_Circuits/ch8.ipynb deleted file mode 100755 index 0309b1db..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch8.ipynb +++ /dev/null @@ -1,561 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:49ff0cb528d7e276dc193290984b83a2a7d93cab62d6ab90be1af99e7320d3ef" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 8:Small Signal Amplifiers" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 8.1 Page no.271" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Ic=2*10**(-3) #A, collector current\n", - "Vce=8.5 #V, collectoe emitter voltage\n", - "\n", - "#Calculation\n", - "#hfe=delta(ic)/delta(ib), #forward current ratio in CE mode\n", - "#Vce=constant #collector emitter voltage\n", - "hfe=(2.7-1.7)*10**(-3)/((20-10)*10**(-6))\n", - "#hoe=delta(ic)/delta(Vce), #output admittance in CE mode\n", - "#ib=constant\n", - "hoe=(2.2-2.1)*10**(-3)/(10-7)\n", - "#hie=delta(Vbe)/delta(ib), #dynamic input resistance\n", - "#Vce=constant\n", - "hie=(0.73-0.715)/((20-10)*10**(-6))\n", - "#hre=delta(Vbe)/delta(Vce),ib=constant #reverse voltage ratio in CE mode\n", - "hre=(0.73-0.72)/(20-0)\n", - "\n", - "#Result\n", - "print \"hfe = \",hfe\n", - "print \"hoe = \",round(hoe/10**(-6),2),\"microS\"\n", - "print \"hie = \",hie/10**3,\"kohm\"\n", - "print \"hre = \",hre\n", - "\n", - "#a) Plot\n", - "#Load Line \n", - "Vce0=[0,15]\n", - "Ic0=[5,0]\n", - "a0=plot(Vce0,Ic0)\n", - "q1=plot(8.5,2.1,label='Q point',marker='o')\n", - "legend()\n", - "# AT Ib=0 microA\n", - "Vce1=[0,1,15]\n", - "Ic1=[0,0.2,0.7]\n", - "a1=plot(Vce1,Ic1)\n", - "# AT Ib=10 microA\n", - "Vce2=[0,1,15]\n", - "Ic2=[0,1.2,1.9]\n", - "a2=plot(Vce2,Ic2)\n", - "# AT Ib=20 microA\n", - "Vce3=[0,1,15]\n", - "Ic3=[0,2.2,3]\n", - "a3=plot(Vce3,Ic3)\n", - "# AT Ib=30 microA\n", - "Vce4=[0,1,15]\n", - "Ic4=[0,3.1,4.1]\n", - "a4=plot(Vce4,Ic4)\n", - "# AT Ib=40 microA\n", - "Vce5=[0,1,15]\n", - "Ic5=[0,4.1,5]\n", - "a5=plot(Vce5,Ic5)\n", - "# AT Ib=50 microA\n", - "Vce6=[0,1,15]\n", - "Ic6=[0,5.1,6.1]\n", - "a6=plot(Vce6,Ic6)\n", - "# AT Ib=60 microA\n", - "Vce7=[0,1,15]\n", - "Ic7=[0,6.1,7.2]\n", - "a7=plot(Vce7,Ic7)\n", - "#At Vce=8.5 V\n", - "Vce8=[0,15]\n", - "Ice8=[2.7,2.7]\n", - "a8=plot(Vce8,Ice8)\n", - "\n", - "Vce9=[0,15]\n", - "Ice9=[1.7,1.7]\n", - "a9=plot(Vce9,Ice9)\n", - "#at Vce=8.5\n", - "Vce10=[8.5,8.5]\n", - "Ice10=[0,3]\n", - "a10=plot(Vce10,Ice10)\n", - "xlim(0,18)\n", - "ylim(0,8)\n", - "xlabel(\"$Vce(volt)$\")\n", - "ylabel(\"$Ic(mA)$\")\n", - "show(q1)\n", - "show(a0)\n", - "show(a1)\n", - "show(a2)\n", - "show(a3)\n", - "show(a4)\n", - "show(a5)\n", - "show(a6)\n", - "show(a7)\n", - "show(a8)\n", - "show(a9)\n", - "show(a10)\n", - "\n", - "#(b) Plot\n", - "#Plot\n", - "#Load Line \n", - "Vce0=[0,15]\n", - "Ic0=[5,0]\n", - "a0=plot(Vce0,Ic0)\n", - "# AT Ib=0 microA\n", - "Vce1=[0,1,15]\n", - "Ic1=[0,0.2,0.7]\n", - "a1=plot(Vce1,Ic1)\n", - "# AT Ib=10 microA\n", - "Vce2=[0,1,15]\n", - "Ic2=[0,1.2,1.9]\n", - "a2=plot(Vce2,Ic2)\n", - "# AT Ib=20 microA\n", - "Vce3=[0,1,15]\n", - "Ic3=[0,2.2,3]\n", - "a3=plot(Vce3,Ic3)\n", - "# AT Ib=30 microA\n", - "Vce4=[0,1,15]\n", - "Ic4=[0,3.1,4.1]\n", - "a4=plot(Vce4,Ic4)\n", - "# AT Ib=40 microA\n", - "Vce5=[0,1,15]\n", - "Ic5=[0,4.1,5]\n", - "a5=plot(Vce5,Ic5)\n", - "# AT Ib=50 microA\n", - "Vce6=[0,1,15]\n", - "Ic6=[0,5.1,6.1]\n", - "a6=plot(Vce6,Ic6)\n", - "# AT Ib=60 microA\n", - "Vce7=[0,1,15]\n", - "Ic7=[0,6.1,7.2]\n", - "a7=plot(Vce7,Ic7)\n", - "\n", - "#At Vce=8.5 V\n", - "Vce8=[0,8.5,10]\n", - "Ice8=[2.2,2.2,2.15]\n", - "a8=plot(Vce8,Ice8)\n", - "# and\n", - "Vce9=[0,8.5,10]\n", - "Ice9=[2.1,2.1,2.15]\n", - "a9=plot(Vce9,Ice9)\n", - "#at Vce=8.5\n", - "Vce10=[8.5,8.5]\n", - "Ice10=[0,2.2]\n", - "a10=plot(Vce10,Ice10)\n", - "\n", - "#at Vce=7 V\n", - "Vce11=[7,7]\n", - "Ice11=[0,2.5]\n", - "a11=plot(Vce11,Ice11)\n", - "#at Vce=10 V\n", - "Vce12=[10,10]\n", - "Ice12=[0,2.2]\n", - "a12=plot(Vce12,Ice12)\n", - "\n", - "q2=plot(8.5,2.15,marker='o',label='Q point')\n", - "legend()\n", - "\n", - "xlim(0,18)\n", - "ylim(0,8)\n", - "xlabel(\"$Vce(volt)$\")\n", - "ylabel(\"$Ic(mA)$\")\n", - "show(a0)\n", - "show(q2)\n", - "show(a1)\n", - "show(a2)\n", - "show(a3)\n", - "show(a4)\n", - "show(a5)\n", - "show(a6)\n", - "show(a7)\n", - "show(a8)\n", - "show(a9)\n", - "show(a10)\n", - "show(a11)\n", - "show(a12)\n", - "\n", - "#C) plot\n", - "#at Vce=0 V\n", - "Vbe1=[0.715,0.730,0.735]\n", - "Ib1=[10,20,30]\n", - "ab1=plot(Vbe1,Ib1)\n", - "q3=plot(0.722,15,marker='o',label='Q Point')\n", - "legend()\n", - "\n", - "#at Vce=8.5 V\n", - "Vbe2=[0.710,0.715,0.730,0.735]\n", - "Ib2=[5,10,20,26]\n", - "ab2=plot(Vbe2,Ib2)\n", - "\n", - "#at Vce=20 V\n", - "Vbe3=[0.6,0.715,0.730,0.740]\n", - "Ib3=[0,10,15,22]\n", - "ab3=plot(Vbe3,Ib3)\n", - "\n", - "#at Ib=10 microA\n", - "Vbe4=[0,0.7,0.75]\n", - "Ib4=[10,10,10]\n", - "ab4=plot(Vbe4,Ib4)\n", - "\n", - "#at Ib=15 microA\n", - "Vbe5=[0,0.7,0.75]\n", - "Ib5=[15,15,15]\n", - "ab5=plot(Vbe5,Ib5)\n", - "#at Ib=20microA\n", - "Vbe6=[0,0.7,0.75]\n", - "Ib6=[20,20,20]\n", - "ab6=plot(Vbe6,Ib6)\n", - " \n", - "xlim(0,0.8)\n", - "ylim(0,35)\n", - "xlabel(\"$Vbe(volt)$\")\n", - "ylabel(\"$Ib(microA)$\")\n", - "show(ab1)\n", - "show(q3)\n", - "show(ab2)\n", - "show(ab3)\n", - "show(ab4)\n", - "show(ab5)\n", - "show(ab6)\n", - "\n", - "#d) plot\n", - "#at Vce=0 V\n", - "Vbe1=[0.6,0.7,0.72,0.73]\n", - "Ib1=[0,6,15,30]\n", - "ab_1=plot(Vbe1,Ib1)\n", - "q4=plot(0.72,15,marker='o',label='$Q Point$')\n", - "legend()\n", - "#Vce=20 V\n", - "Vbe2=[0.6,0.7,0.72,0.73,0.74]\n", - "Ib2=[0,6,10,15,28]\n", - "ab_2=plot(Vbe2,Ib2)\n", - "#At Ib=15 microA\n", - "Vbe3=[0,0.72,0.73]\n", - "Ib3=[15,15,15]\n", - "ab_3=plot(Vbe3,Ib3)\n", - "\n", - "#At Vbe=0.72\n", - "Vbe4=[0.72,0.72]\n", - "Ib4=[0,15]\n", - "ab_4=plot(Vbe4,Ib4)\n", - "#At Vbe=0.73\n", - "Vbe5=[0.73,0.73]\n", - "Ib5=[0,15]\n", - "ab_5=plot(Vbe5,Ib5)\n", - "\n", - "xlim(0,0.8)\n", - "ylim(0,35)\n", - "xlabel(\"$Vbe(volt)$\")\n", - "ylabel(\"$Ib(microA)$\")\n", - "show(ab_1)\n", - "show(q4)\n", - "show(ab_2)\n", - "show(ab_3)\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "hfe = 100.0\n", - "hoe = 33.33 microS\n", - "hie = 1.5 kohm\n", - "hre = 0.0005\n" - ] - }, - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAESCAYAAAD0aQL3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nFCUAQgjxUJQACCHEQ1ECIIQQD/X/AAoZUTqTRcPQAAAAAElFTkSuQmCC\n" - }, - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAESCAYAAAD0aQL3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfooSACGE+ClKAIQQ4qcoARBCiJ/6/6jf3NEk5ghMAAAAAElFTkSuQmCC\n" - }, - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAESCAYAAADnvkIDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLAgiItKJBUFERDr9f+uLfdE892zcAAAAAElFTkSuQmCC\n" - }, - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAESCAYAAADnvkIDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nREQasSCIiEgjFgQREWnEgiAiIo3+P8ixPOMqV0GTAAAAAElFTkSuQmCC\n" - } - ], - "prompt_number": 50 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 8.2 Page no.276" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "ri=2000.0 #Ohms, input resistance\n", - "Rb=150000.0 #Ohms, base resistance\n", - "\n", - "#Calculation\n", - "Zin=Rb*ri/(Rb+ri)\n", - "\n", - "#result\n", - "print \" The Input Impedance of the Amplifier is Zin = \",round(Zin/10**3,3),\"kohm\"\n", - "\n", - "#(b)find the voltage gain (Av)\n", - "Beeta=100\n", - "ri=2000.0 #Ohms\n", - "Rac=5000.0 #Ohms Resistance on outputside\n", - "\n", - "#Calculation\n", - "\n", - "Av=Beeta*Rac/ri\n", - "#result\n", - "\n", - "print \" The Voltage Gain of the Amplifier with phase of pi/2 is \",Av\n", - "#(c) find the current gain (Ai)\n", - "#Let input Current ib=2A\n", - "ib=2 #A, Assumption\n", - "io=100*ib \n", - "\n", - "#Calculation\n", - "Ai=io/ib # Current Gain\n", - "#result\n", - "print \"The Current Gain of the Amplifier is Ai = \",Ai" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Input Impedance of the Amplifier is Zin = 1.974 kohm\n", - " The Voltage Gain of the Amplifier with phase of pi/2 is 250.0\n", - "The Current Gain of the Amplifier is Ai = 100\n" - ] - } - ], - "prompt_number": 7 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 8.3 Page no.277" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Bac=150.0 #ac current gain\n", - "rin=2000.0 #Ohms, input resistance\n", - "R1=4700.00 #Ohms, resistance\n", - "R2=12000.0 #Ohms resistance\n", - "\n", - "#Calculation\n", - "Rac=R1*R2/(R1+R2) # ohm , resistance\n", - "Av=Bac*Rac/rin\n", - "#result\n", - "print \"a\"\n", - "print \"the Voltage Gain of the Amplifier with phase of pi/2 is\",round(Av,1)\n", - "\n", - "#(b)find input impedance\n", - "R3=75000.0 #Ohms\n", - "R4=7500.00 #Ohms\n", - "\n", - "#Calculation\n", - "Zin=R3*R4*rin/(R3*R4+R4*rin+rin*R3)\n", - "\n", - "#result\n", - "print \"b\"\n", - "print \"The Input Impedance of the Amplifier is Zin = \",round(Zin/10**3,1),\"kohm\"\n", - "\n", - "#(c)Q point\n", - "\n", - "Vcc=15 #V\n", - "R1=75000.0 #Ohms\n", - "R2=7500.00 #Ohms\n", - "Rc=4700.0 #Ohms\n", - "Re=1200.0 #Ohms\n", - "\n", - "#Calculation\n", - "Vb=Vcc*R2/(R1+R2) #V, base voltage\n", - "Ve=Vb\n", - "Ie=Ve/Re #A, emitter current\n", - "Vce=Vcc-(Rc+Re)*Ie #V, collector emitter voltage\n", - "#result\n", - "print \"c\"\n", - "print \"voltage at the base is \",round(Vb,2),\"V\"\n", - "print \"Emitter current is \",round(Ie/10**(-3),2),\"mA\"\n", - "print \"The collector to emitter voltage is\",round(Vce,2),\"v\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "a\n", - "the Voltage Gain of the Amplifier with phase of pi/2 is 253.3\n", - "b\n", - "The Input Impedance of the Amplifier is Zin = 1.5 kohm\n", - "c\n", - "voltage at the base is 1.36 V\n", - "Emitter current is 1.14 mA\n", - "The collector to emitter voltage is 8.3 v\n" - ] - } - ], - "prompt_number": 7 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 8.4 Page no.283" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "u=20 #amplification factor\n", - "Rl=10*10**3 #Ohms, load resistance\n", - "rp=10*10**3 #Ohms, resistance\n", - "#Calculation\n", - "A=u*Rl/(rp+Rl) #V, voltage gain\n", - "#result\n", - "print \" The Voltage Gain of the Amplifier with phase of pi/2 is\",A" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 8.5 Page no.286" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "gm=3000*10**(-6) #S, transconductance\n", - "Rl=22*10**3 #Ohms, resistance\n", - "rp=300*10**3 #Ohms, resistance \n", - "\n", - "#Calculation\n", - "#A=-(gm*Rl/(1+(Rl/rp))), For rp>>Rl we get\n", - "A=gm*Rl #with Phase of 180 degrees\n", - "# Results \n", - "print \"The Gain of the Amplifier with phase of pi/2 is\",A" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "The Gain of the Amplifier with phase of pi/2 is 66.0\n" - ] - } - ], - "prompt_number": 8 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 8.6 Page no.286" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Rl=12000.0 #Ohms, load resistance\n", - "Rg=1000000.0 #Ohms, given resistance\n", - "Rs=1*10**3 #Ohms, given resistance\n", - "Cs=25*10**(-6) #F. capacitance\n", - "u=20 #amplification factor\n", - "rd=10**5 #Ohms, dynamic drain resistance\n", - "vi=0.1 #V, input voltage\n", - "f=1*10**3 #Hz, frequency\n", - "\n", - "#Calculation\n", - "import math\n", - "Xcs=1/(2*math.pi*f*Cs)\n", - "#As Xcs comes out to be much smaller than Rs, Rs is completely bypassed\n", - "A=u*Rl/(Rl+rd)\n", - "vo=A*vi\n", - "# Result\n", - "print \" The Output Signal Voltage of the Amplifier is vo = \",round(vo,3),\"v\"\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Output Signal Voltage of the Amplifier is vo = 0.214 v\n" - ] - } - ], - "prompt_number": 2 - }, - { - "cell_type": "code", - "collapsed": false, - "input": [], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file diff --git a/Basic_Electronics_and_Linear_Circuits/ch9.ipynb b/Basic_Electronics_and_Linear_Circuits/ch9.ipynb deleted file mode 100755 index 3b1261da..00000000 --- a/Basic_Electronics_and_Linear_Circuits/ch9.ipynb +++ /dev/null @@ -1,254 +0,0 @@ -{ - "metadata": { - "name": "", - "signature": "sha256:83bf55a24e2aa90db4083899e2e7c0a6deddf51b02a3e4634d291129436942ec" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ - { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Chapter 9:Multi stage Amplifiers" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 9.1 Page no.305" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "A1=30 #voltage gain 1\n", - "A2=50 #voltage gain 2\n", - "A3=80 #voltage gain 3\n", - "\n", - "#Calculation\n", - "import math\n", - "A=A1*A2*A3 #overall Voltage Gain\n", - "Adb=20*math.log10(A) #Voltage Gain in dB\n", - "# Result\n", - "print \" The overall Voltage Gain of the Multistage Amplifier Adb = \",round(Adb,2),\"dB\"" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The overall Voltage Gain of the Multistage Amplifier Adb = 101.58 dB\n" - ] - } - ], - "prompt_number": 1 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 9.2 Page no.312" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Vcc=30.0 #V, collector bias junction voltage\n", - "Vi=1.4 #V, input voltage\n", - "Vbe=0.7 #V. base emitter voltage \n", - "B=300 #Beeta, gain factor\n", - "R1=27000.0 #Ohms, given resistance\n", - "R2=680.0 #Ohms given resistance\n", - "R3=24000.0 #Ohms\n", - "R4=2400.0 #Ohms\n", - "\n", - "#Calculation\n", - "Ve=Vi-Vbe #V, voltage at emitter terminal\n", - "Ie1=Vbe/R2 #A, emitter current at 1st stage\n", - "Ic1=Ie1 #A, collector current\n", - "Vc1=Vcc-round(Ie1,3)*R1 #collector voltage at 1st stage\n", - "Vb2=Vc1 #V, base voltage at 2nd stage\n", - "\n", - "Ve2=Vb2-Vbe #V emitter voltage at 2nd stage\n", - "Ie2=Ve2/R4 #A, emitter current at 2nd stage\n", - "Ic2=round(Ie2,3) #A collector current at 2nd stage\n", - "Vc2=Vcc-Ic2*R3\n", - "Vo=Vc2\n", - "#Displaying The Results in Command Window\n", - "print \" The Voltage at the Output Terminal of Two Stage Direct Coupled Amplifier, Vo = \",Vo,\"V\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 9.3 Page no.319" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "A=100 #voltage gain\n", - "f1=400 #Hz, frequency 1\n", - "f2=25*10**3 #Hz, frequency 2\n", - "f3=80 #Hz, frequency 3 \n", - "f4=40*10**3 # Hz, frequency 4 \n", - "\n", - "#Calculation\n", - "import math\n", - "Adb=20*math.log10(A)\n", - "Adbc=Adb-3 #Lower by 3dB\n", - "# Result\n", - "print \" The Gain at Cutoff Frequencies is, Adb (at Cutoff Frequencies) = \",Adbc,\"dB\"\n", - "\n", - "#plot\n", - "from pylab import *\n", - "f1=[80,400,25000,40000]\n", - "Adb1=[37,40,40,37]\n", - "a=plot(f1,Adb1)\n", - "xlim(0,40000)\n", - "xlabel(\"$f(Hz)$\")\n", - "ylabel(\"$AdB$\")\n", - "ylim(0,50)\n", - "show(a1)\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - " The Gain at Cutoff Frequencies is, Adb (at Cutoff Frequencies) = 37.0 dB\n" - ] - }, - { - "metadata": {}, - "output_type": "display_data", - "png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAESCAYAAAABl4lHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n" - } - ], - "prompt_number": 8 - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 9.4 Page no 325." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - " #all the quantities of R are resistances\n", - "R1=5600.0 #Ohms\n", - "R2=56000.0 #Ohms\n", - "R3=1100.0 #Ohms\n", - "\n", - "#Calculation\n", - "Zi=R1*R2*R3/(R1*R2+R2*R3+R3*R1)\n", - "#Result\n", - "print \" The Input Impedance, Zi = \",round(Zi/10**3,3),\"kohm\"\n", - "\n", - "#(b) Calculate output Impedance \n", - "Ro1=3300.0 #Ohms\n", - "Ro2=2200 #Ohms\n", - "\n", - "#Calculation\n", - "Zo=Ro1*Ro2/(Ro1+Ro2)\n", - "\n", - "#Result\n", - "print \" The Output Impedance, Zo = \",Zo/10**3,\"kohm\"\n", - "#(c) voltage gain\n", - "hfe=120 #current amplification factor\n", - "hie=1100.0 #Ohms, dynamic input resistance\n", - "R1=6800.0 #Ohms\n", - "R2=56000.0 #Ohms\n", - "R3=5600.0 #Ohms\n", - "R4=1100.0 #Ohms\n", - "\n", - "#Calculation\n", - "Rac2=Ro1*Ro2/(Ro1+Ro2)\n", - "A2=-hfe*Rac2/hie\n", - "Rac1=R1*R2*R3*R4/(R1*R2*R3+R2*R3*R4+R1*R3*R4+R1*R2*R4)\n", - "Rac1=round(Rac1,0)\n", - "A1=-hfe*Rac1/hie\n", - "\n", - "A1=round(A1,2)\n", - "A=A1*A2 #Overall Gain\n", - "\n", - "#Result\n", - "print \" The Overall Gain, A = \",round(A,0)" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Example 9.5 Page no. 326" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "Rl=10000.0 #Ohms, resistance\n", - "Rg=470000.0 #Ohms dynamic input resistance\n", - "Cs=100*10**(-12) #F Capacitance\n", - "u=25 #amplification factor\n", - "rp=8000.0 #Ohms\n", - "Cc=0.01*10**(-6) #F, capacitance\n", - "\n", - "#Calculation\n", - "import math\n", - "gm=u/rp #transconductance\n", - "Req=rp*Rl*Rg/(rp*Rl+Rl*Rg+Rg*rp) #equivalent resistance\n", - "Avm=(u/rp)*Req #voltage gain\n", - "Avmd=Avm**2 # Voltage Gain of Two Stages\n", - "Rd=(rp*Rl/(rp+Rl))+Rg\n", - "f1=1/(2*math.pi*Cc*Rd) #Lower Cutoff Frequency\n", - "f1d=f1/math.sqrt(math.sqrt(2)-1) #Lower Cutoff Frequency of Two Stages\n", - "Req =(rp*Rl)/(rp+Rl) #approximately\n", - "f2=1/(2*math.pi*Cs*Req) #Upper Cutoff Frequency\n", - "f2d=f2*math.sqrt(math.sqrt(2)-1) #Upper Cutoff Frequency of Two Stages\n", - "BW=f2d-f1d \n", - "#Bandwidth\n", - "# Result\n", - "print \" The Voltage Gain of Two Stages, Avmd = \",round(Avmd,2)\n", - "print \" The Bandwidth, BW = \",round(BW/10**3,0),\"KHz\"" - ], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} - } - ] -}
\ No newline at end of file |