{
 "metadata": {
  "name": "Chapter_14"
 }, 
 "nbformat": 2, 
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown", 
     "source": [
      "<h1>Chapter 14: Special-purpose Op-amp cicuits<h1>"
     ]
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.1, Page Number: 458<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "%matplotlib inline"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "", 
        "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].", 
        "For more information, type 'help(pylab)'."
       ]
      }
     ], 
     "prompt_number": 1
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "R1=25*10**3;", 
      "R2=R1;", 
      "A_cl=500;    #closed loop voltage gain", 
      "R_G=2*R1/(A_cl-1);", 
      "print('value of the external gain setting resistor in ohms = %d'%R_G)"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "value of the external gain setting resistor in ohms = 100"
       ]
      }
     ], 
     "prompt_number": 2
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.2, Page Number: 460<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "R1=25.25*10**3;    #internal resistors", 
      "R2=R1;", 
      "R_G=510.0;", 
      "A_v=(2*R1/R_G)+1;", 
      "print('voltage gain = %f'%A_v)", 
      "BW=60.0*10**3;", 
      "print('bandwidth from graph = %d hertz'%BW)"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "voltage gain = 100.019608", 
        "bandwidth from graph = 60000 hertz"
       ]
      }
     ], 
     "prompt_number": 3
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.3, Page Number: 462<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "R_f1=22.0*10**3;", 
      "R_i1=2.2*10**3;", 
      "R_f2=47.0*10**3;", 
      "R_i2=10.0*10**3;", 
      "A_v1=(R_f1/R_i1)+1;    #voltage gain of input stage", 
      "A_v2=(R_f2/R_i2)+1;    #voltage gain of output stage", 
      "A_v=A_v1*A_v2;", 
      "print('total voltage gain of the isolation amplifier = %.1f'%A_v)"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "total voltage gain of the isolation amplifier = 62.7"
       ]
      }
     ], 
     "prompt_number": 4
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.5, Page Number: 466<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "g_m=1000.0*10**-6;", 
      "V_in=25*10**-3;", 
      "I_out=g_m*V_in;", 
      "print('output current = %f A'%I_out)"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "output current = 0.000025 A"
       ]
      }
     ], 
     "prompt_number": 5
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.6, Page Number: 468<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "V_BIAS=9.0;", 
      "V=V_BIAS;", 
      "R_BIAS=33.0*10**3;", 
      "R_L=10.0*10**3;", 
      "K=16.0;    #in microSiemens per microAmpere", 
      "I_BIAS=(V_BIAS-(-V)-1.4)/R_BIAS;", 
      "g_m=K*I_BIAS;", 
      "A_v=g_m*R_L;", 
      "print('voltage gain = %f'%A_v)"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "voltage gain = 80.484848"
       ]
      }
     ], 
     "prompt_number": 6
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.7, Page Number: 469<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "import pylab", 
      "import numpy ", 
      "", 
      "", 
      "V_MOD_max=10.0;", 
      "V_MOD_min=1.0;", 
      "V=9.0;", 
      "V_in=50.0*10**-3;", 
      "R_BIAS=56.0*10**3;", 
      "R_L=10.0*10**3;", 
      "K=16.0;    #in microSiemens per microAmpere", 
      "I_BIAS_max=(V_MOD_max-(-V)-1.4)/R_BIAS;", 
      "", 
      "g_m_max=K*I_BIAS_max;", 
      "A_v_max=g_m_max*R_L;", 
      "V_out_max=A_v_max*V_in;", 
      "", 
      "I_BIAS_min=(V_MOD_min-(-V)-1.4)/R_BIAS;", 
      "", 
      "g_m_min=K*I_BIAS_min;", 
      "A_v_min=g_m_min*R_L;", 
      "V_out_min=A_v_min*V_in;", 
      "", 
      "###############PLOT#############################", 
      "f=1.0;    #assume frequency 1 hertz", 
      "t = arange(0.0001, 4.0, 0.0005)", 
      "y=(((V_out_max/4)-(V_out_min/4))*sin(2*pi*f*t)+((V_out_min/2)+(V_out_max/2))/2)*sin(2*9*pi*f*t);", 
      "", 
      "plot(t,y)", 
      "plot(t,0.61*t/t,'r')", 
      "plot(t,-0.61*t/t,'r')", 
      "ylim( (-2,2) )", 
      "ylabel('Vout')", 
      "title('Modulated Output Voltage')"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "pyout", 
       "prompt_number": 7, 
       "text": [
        "<matplotlib.text.Text at 0xa98084c>"
       ]
      }, 
      {
       "output_type": "display_data", 
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6yFqGMtfdIuoPUPITp+9egYKNQNYBYFoFgBWRMsM/AYa08feKDgInFAMweWgZ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\noMS/KVKkmvD3qkwAAAAASUVORK5CYII=\n"
      }
     ], 
     "prompt_number": 7
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.8, Page Number: 473<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "import math", 
      "V_in=2;", 
      "I_R=50.0*10**-9;", 
      "R1=100.0*10**3;", 
      "#voltage output for log amplifier", 
      "V_OUT=-0.025*math.log(V_in/(I_R*R1));", 
      "print('output voltage = %f volts'%V_OUT)"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "output voltage = -0.149787 volts"
       ]
      }
     ], 
     "prompt_number": 8
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.9, Page Number: 474<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "import math", 
      "V_in=3;", 
      "I_EBO=40*10**-9;", 
      "R1=68*10**3;", 
      "#voltage output for log amplifier", 
      "V_OUT=-0.025*math.log(V_in/(I_EBO*R1));", 
      "print('output voltage = %f Volts'%V_OUT)"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "output voltage = -0.175143 Volts"
       ]
      }
     ], 
     "prompt_number": 9
    }, 
    {
     "cell_type": "markdown", 
     "source": [
      "<h3>Example 14.10, Page Number: 475<h3>"
     ]
    }, 
    {
     "cell_type": "code", 
     "collapsed": false, 
     "input": [
      "", 
      "import math", 
      "I_EBO=40.0*10**-9;", 
      "V_in=175.1*10**-3;", 
      "R_f=68.0*10**3;", 
      "V_OUT=-I_EBO*R_f*math.exp(V_in/0.025);", 
      "print('output voltage = %f Volts'%V_OUT)"
     ], 
     "language": "python", 
     "outputs": [
      {
       "output_type": "stream", 
       "stream": "stdout", 
       "text": [
        "output voltage = -2.994797 Volts"
       ]
      }
     ], 
     "prompt_number": 10
    }
   ]
  }
 ]
}