path: root/Analog_Integrated_Circuits_by_J._B._Gupta/Chaper04.ipynb

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  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Chapter -4 Linear Applications of Op-Amps"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.1 - Page 111"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Given data\n",
      "Vout= '-(V1+10*V2+100*V3)' #given expression  \n",
      "Rf= 100 # in k\u03a9\n",
      "# Vout= -Rf*(V1/R1+V2/R2+V3/R3)= -(Rf/R1*V1+Rf/R2*V2+Rf/R3*V3)     (i)\n",
      "# Compare equation(i) with given expression\n",
      "R1= Rf/1 #in k\u03a9\n",
      "R2= Rf/10 # in k\u03a9\n",
      "R3= Rf/100 # in k\u03a9\n",
      "print \"The value of Rf = %0.f k\u03a9\" %Rf\n",
      "print \"The value of R1 = %0.f k\u03a9\" %R1\n",
      "print \"The value of R2 = %0.f k\u03a9\" %R2\n",
      "print \"The value of R3 = %0.f k\u03a9\" %R3"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The value of Rf = 100 k\u03a9\n",
        "The value of R1 = 100 k\u03a9\n",
        "The value of R2 = 10 k\u03a9\n",
        "The value of R3 = 1 k\u03a9\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.2 - Page 112"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import division\n",
      "# Given data\n",
      "Rf= 12 # in k\u03a9\n",
      "R1= 12 # in k\u03a9\n",
      "R2= 2 # in k\u03a9\n",
      "R3= 3 # in k\u03a9\n",
      "V1= 9 # in V\n",
      "V2= -3 # in V\n",
      "V3= -1 # in V\n",
      "Vout= -Rf*(V1/R1+V2/R2+V3/R3) # output voltage in V\n",
      "print \"The output voltage = %0.f V\" %Vout"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The output voltage = 13 V\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.3 - Page 112"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Given data\n",
      "Vout= '(-V1+2*V2-3*V3)' #given expression  \n",
      "Rf= 6 # in k\u03a9\n",
      "# Vout=  -(Rf/R1*V1+Rf/R2*V2+Rf/R3*V3)     (i)\n",
      "# Compare equation(i) with given expression\n",
      "R1= Rf/1 #in k\u03a9\n",
      "R2= Rf/2 # in k\u03a9\n",
      "R3= Rf/3 # in k\u03a9\n",
      "print \"The value of Rf = %0.f k\u03a9\" %Rf\n",
      "print \"The value of R1 = %0.f k\u03a9\" %R1\n",
      "print \"The value of R2 = %0.f k\u03a9\" %R2\n",
      "print \"The value of R3 = %0.f k\u03a9\" %R3"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The value of Rf = 6 k\u03a9\n",
        "The value of R1 = 6 k\u03a9\n",
        "The value of R2 = 3 k\u03a9\n",
        "The value of R3 = 2 k\u03a9\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.4 - Page 112"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Given data\n",
      "Vout= '(-2*V1+3*V2+4*V3)' #given expression  \n",
      "R3= 10 # in k\u03a9\n",
      "# Vout=  -(Rf/R1*V1+Rf/R2*V2+Rf/R3*V3)     (i)\n",
      "# Compare equation(i) with given expression\n",
      "Rf= 4*R3 #in k\u03a9\n",
      "R2= Rf/3 # in k\u03a9\n",
      "R1= Rf/2 # in k\u03a9\n",
      "print \"The value of Rf = %0.f k\u03a9\" %Rf\n",
      "print \"The value of R2 = %0.2f k\u03a9\" %R2\n",
      "print \"The value of R1 = %0.f k\u03a9\" %R1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The value of Rf = 40 k\u03a9\n",
        "The value of R2 = 13.33 k\u03a9\n",
        "The value of R1 = 20 k\u03a9\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.5 - Page 113"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "V1= 2 # in V\n",
      "V2= -1 # in V\n",
      "R=100 # in \u03a9 (assumed)\n",
      "Vs1= V1*(R/2)/(R+R/2) # in V\n",
      "Rf= 2*R # in \u03a9\n",
      "Vo_1= Vs1*(1+Rf/R) # in V\n",
      "Vs2= V2*(R/2)/(R+R/2) # in V\n",
      "Vo_2= Vs2*(1+Rf/R) # in V\n",
      "Vout= Vo_1+Vo_2 #output voltage in V\n",
      "print \"The output voltage = %0.f V\" %Vout"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The output voltage = 1 V\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.7 - Page 118"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Given data\n",
      "Vin= 10 # in V\n",
      "R= 2.2 # in k\u03a9\n",
      "R= R*10**3 # in k\u03a9\n",
      "Ad= 10**5 # differential voltage gain\n",
      "C=1 # in \u00b5F\n",
      "C= C*10**-6 # in F\n",
      "T= 1 # in ms\n",
      "T= T*10**-3 # in s\n",
      "I= Vin/R # in mA\n",
      "V= I*T/C # output voltage at the end of pulse in mV\n",
      "print \"The output voltage at the end of the pulse = %0.3f V\" %V\n",
      "RC_desh= R*C*Ad # closed-loop time constant in sec.\n",
      "print \"The closed-loop time constant = %0.f seconds\" %RC_desh"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The output voltage at the end of the pulse = 4.545 V\n",
        "The closed-loop time constant = 220 seconds\n"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.8 - Page 119"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Given data\n",
      "A_dB= 20 # peak gain in dB\n",
      "A= 10**(A_dB/20) # peak gain\n",
      "omega= 10000 # in rad/second\n",
      "C= 0.01 # in \u00b5F\n",
      "C= C*10**-6 # in F\n",
      "Rf= 10 # in k\u03a9\n",
      "# Vout/V1= Rf/R1= A\n",
      "R1= Rf/A # in k\u03a9\n",
      "print \"The value of Rf = %0.f k\u03a9\" %Rf\n",
      "print \"The value of R1 = %0.f k\u03a9\" %R1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The value of Rf = 10 k\u03a9\n",
        "The value of R1 = 1 k\u03a9\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.9 - Page 119"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import numpy as np\n",
      "from scipy.integrate import quad\n",
      "from sympy import symbols\n",
      "import matplotlib.pyplot as plt\n",
      "from matplotlib.pylab import plot, show, ylim, xlim, text, subplot\n",
      "a= symbols('a')\n",
      "# Given data\n",
      "R= 40 # in k\u03a9\n",
      "R= R*10**3 # in \u03a9\n",
      "C= 0.2 # in \u00b5F\n",
      "C= C*10**-6 # in F\n",
      "Vin= 5 # in V\n",
      "V1= 3 # in V\n",
      "t= 50 # in ms\n",
      "Vout= 3 # in V\n",
      "# Evaluation the integration\n",
      "def integrand(x):\n",
      "    return (Vin-V1)\n",
      "a=1\n",
      "ans, err = quad(integrand, 0, 50)\n",
      "# Output voltage when swith is open\n",
      "vout= -1/(R*C)*ans*10**-3+Vout #in V\n",
      "plt.plot([0,t],[Vout,vout]) \n",
      "plt.title('Output voltage') \n",
      "plt.xlabel('Time in milliseconds')\n",
      "plt.ylabel('Output voltage in volts')\n",
      "plt.show()\n",
      "print \"Plot for output voltage shown in figure\" "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
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8EhMT9XY9UxYQIFeXfeUVuS7U5Mlyv20iorqqNUlkZmZWel1aWor09HS9BZSbmwunCjvw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\nTBJERFQjJgkiIqoRkwQREdXo/wFhQuAL9Tcf7gAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f46831f7110>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Plot for output voltage shown in figure\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.10 - Page 120"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from scipy.integrate import quad\n",
      "import numpy as np\n",
      "# Given data\n",
      "R= 500 # in k\u03a9\n",
      "R= R*10**3 # in \u03a9\n",
      "C= 10 # in \u00b5F\n",
      "C= C*10**-6 # in F\n",
      "vout= 12 # in V\n",
      "v= -0.5 # in V\n",
      "# given output equation : vout= -1/RC * integrate[v(t) * dt + A] \n",
      "# Evaluation the integration\n",
      "def integrand(t):\n",
      "    return -t\n",
      "ans, err = quad(integrand, 0, 1)\n",
      "vout_by_t= -1/(R*C)*ans #in V/sec\n",
      "# Time required for saturation of output voltage\n",
      "t= vout/vout_by_t # in sec\n",
      "print \"The time duration required for saturation of output voltage = %0.f seconds\" %t"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The time duration required for saturation of output voltage = 120 seconds\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.12 - Page 124"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import division\n",
      "%matplotlib inline\n",
      "from sympy import symbols, simplify, sin\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "# Given data\n",
      "fa= 1 # in kHz\n",
      "fa=fa*10**3 # in Hz\n",
      "Vp=1.5 # in volt\n",
      "f= 200 # in Hz\n",
      "C=0.1 # in micro F\n",
      "C=C*10**-6 # in F\n",
      "R= 1/(2*np.pi*fa*C) # in ohm\n",
      "R=R*10**-3 # in k ohm\n",
      "R=np.floor(R*10)/10 # in k ohm\n",
      "fb= 20*fa # in Hz\n",
      "R_desh= 1/(2*np.pi*fb*C) # in ohm\n",
      "# Let\n",
      "R_desh= 82 # in ohm\n",
      "R_OM= R # in k ohm\n",
      "print \"Value of R_OM = %0.1f k ohm\" %R_OM\n",
      "CR= C*R \n",
      "# Vin= Vp*sin(omega*t)= 1.5*sin(400*t)\n",
      "# v_out= -CR*diff(v_in) = -0.2827 Cos(400*pi*t)# in micro volt\n",
      "print \"Output Voltage = -0.2827 Cos(400*pi*t)\" \n",
      "t = np.arange(0, .015, 1.0/44100)\n",
      "v_out=-0.2827*np.sin(400*np.pi*t+np.pi/2)# in micro volt\n",
      "plot(t,v_out) \n",
      "plt.title('Output Voltage Waveform')\n",
      "plt.xlabel('Time in ms')\n",
      "plt.ylabel('Vout in Volts') \n",
      "print \"Output Voltage waveform is shown in figure.\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Value of R_OM = 1.5 k ohm\n",
        "Output Voltage = -0.2827 Cos(400*pi*t)\n",
        "Output Voltage waveform is shown in figure."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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QnZ0tSo7FKDV/YkDrD8Pdu8CFC7zBUiKtWgEFBdpeL6TU/ImBDh1o4oS5COsT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\ngQyFIAiCkIT/D1aoyBiLHf2sAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fbcffdbf150>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Example 4.15 - Page 130"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Given data\n",
      "R1= 50 # in k\u03a9\n",
      "R3=15 # in k\u03a9\n",
      "R4=R3 # in k\u03a9\n",
      "# For minimum differential voltage gain,\n",
      "Ad_min= 5 # and\n",
      "Ad= Ad_min \n",
      "# From Ad= 1+2*R2/R1\n",
      "R2= (Ad-1)*R1/2 # in k\u03a9\n",
      "# For maximum differential voltage gain,\n",
      "Ad_max= 200 # and\n",
      "Ad= Ad_max \n",
      "# From Ad= 1+2*R2/R1\n",
      "R1_min= round(2*R2/(Ad-1)) # in k\u03a9\n",
      "print \"The value of R1 =  %0.f - 50 k\u03a9 potentiometer\" %R1_min\n",
      "print \"The value of R2 = %0.f k\u03a9\" %R2\n",
      "print \"The value of R3 and R4 = %0.f k\u03a9 each\" %R3"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The value of R1 =  1 - 50 k\u03a9 potentiometer\n",
        "The value of R2 = 100 k\u03a9\n",
        "The value of R3 and R4 = 15 k\u03a9 each\n"
       ]
      }
     ],
     "prompt_number": 23
    }
   ],
   "metadata": {}
  }
 ]
}