Fibonacci series using Cortex M4 Assembly

Fibonacci Series:

1 ,1 ,2, 3, 5, 8, 13....

Series can be checked element by element in R4 or in the memory location mentioned.

Code: 

   PRESERVE8
    THUMB
    AREA    |.text|,CODE,READONLY
    EXPORT __main
    ENTRY
__main    FUNCTION
    MOV R0,#0;Initial number 0
    MOV R1,#1;Initial number 1
    MOV R3,#255;Upto What Number you want the series(req)
    MOV R4,#0;every element in series will be stored in r4
    MOV R5,#0x20000000;The entire series is written from this memory location
    ADD R4,R0,R1;val = t0+t1
loop1 CMP R4,R3;if(val > req)
    BLE LOOP;if less goto loop
    B stop;Else goto end 
LOOP STR R4,[R5],#1;Storing the series into memory
    MOV R0,R1;t1=t0;
    MOV R1,R4;t0=val
    ADD R4,R0,R1;val = t0 + t1
    B loop1;Loop untill val >= req
stop    B stop
        ENDFUNC
        END

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Exponential Series in ARM Cortex M4 Assembly

e^x = 1 + (x/1!)+((x^2)/2!)+((x^3)/3!)+......

The below ARM assembly code will be used to find the value of e^x  based on the above definition for any value of x using the Floating point unit of ARM Cortex-M4 Processor.

Code:

 PRESERVE8
        THUMB
        AREA    |.text|,CODE,READONLY
        EXPORT __main
        ENTRY
__main    FUNCTION
        MOV R0,#10;Holding the Number of Terms in Series 'n'
        MOV R1,#1;Counting Variable 'i'
        VLDR.F32 S0,=1;Holding the sum of series elements 's'
        VLDR.F32 S1,=1;Temp Variable to hold the intermediate series elements 't'
        VLDR.F32 S2,=3;Holding 'x' Value
LOOP1    CMP R1,R0;Compare 'i' and 'n' 
        BLE LOOP;if i < n goto LOOP
        B stop;else goto stop
LOOP      VMUL.F32 S1,S1,S2; t = t*x
        VMOV.F32 S5,R1;Moving the bit stream in R1('i') to S5(floating point register)
        VCVT.F32.U32 S5, S5;Converting the bitstream into unsigned fp Number 32 bit
        VDIV.F32 S1,S1,S5;Divide t by 'i' and store it back in 't'
        VADD.F32 S0,S0,S1;Finally add 's' to 't' and store it in 's'
        ADD R1,R1,#1;Increment the counter variable 'i'
        B LOOP1;Again goto comparision
stop    B stop
        ENDFUNC
        END

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Python Language Translator

 

Synopsis:

The Python Language Translator is a python script which takes the input from the user and converts it to any language that user want and read the converted text in that particular language

Execution:

Command : python PyLanguage_Translator.py

Script Link:

 

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Ubuntu News Application

 

 

Synopsis:

The Ubuntu News Application is a python script which takes the input i.e the category of input that user wants the news to be and from that category the script will try to fetch the latest news from the CNN news Website and push the titles of the news as a notification in Ubuntu. 

Execution:

Command : python Ubuntu_News_App.py

Script Link :

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3D - OBJECT DETECTION USING OPENCV-PYTHON

The following Code will detect the object present in the image ,whether it is a Cube or a Cylinder or Sphere based on Contour Approximation.The below Code is written Using the Python API for OpenCV Library.

 Script:

import cv2
# Importing the Opencv Library
import numpy as np
# Importing NumPy,which is the fundamental package for scientific computing with #Python

# Reading Image
img = cv2.imread("/home/whoami/Pictures/cylinder1.jpg")
cv2.namedWindow("Original Image",cv2.WINDOW_NORMAL)
# Creating a Named window to display image
cv2.imshow("Original Image",img)
# Display image

# RGB to Gray scale conversion
img_gray = cv2.cvtColor(img,cv2.COLOR_RGB2GRAY)
cv2.namedWindow("Gray Converted Image",cv2.WINDOW_NORMAL)
# Creating a Named window to display image
cv2.imshow("Gray Converted Image",img_gray)
# Display Image

# Noise removal with iterative bilateral filter(removes noise while preserving edges)
noise_removal = cv2.bilateralFilter(img_gray,9,75,75)
cv2.namedWindow("Noise Removed Image",cv2.WINDOW_NORMAL)
# Creating a Named window to display image
cv2.imshow("Noise Removed Image",noise_removal)
# Display Image
# Thresholding the image
ret,thresh_image = cv2.threshold(noise_removal,0,255,cv2.THRESH_OTSU)
cv2.namedWindow("Image after Thresholding",cv2.WINDOW_NORMAL)
# Creating a Named window to display image
cv2.imshow("Image after Thresholding",thresh_image)
# Display Image

# Applying Canny Edge detection
canny_image = cv2.Canny(thresh_image,250,255)
cv2.namedWindow("Image after applying Canny",cv2.WINDOW_NORMAL)
# Creating a Named window to display image
cv2.imshow("Image after applying Canny",canny_image)
# Display Image
canny_image = cv2.convertScaleAbs(canny_image)

# dilation to strengthen the edges
kernel = np.ones((3,3), np.uint8)
# Creating the kernel for dilation
dilated_image = cv2.dilate(canny_image,kernel,iterations=1)
cv2.namedWindow("Dilation", cv2.WINDOW_NORMAL)
# Creating a Named window to display image
cv2.imshow("Dilation", dilated_image)
# Displaying Image
contours, h = cv2.findContours(dilated_image, 1, 2)
contours= sorted(contours, key = cv2.contourArea, reverse = True)[:1]
pt = (180, 3 * img.shape[0] // 4)
for cnt in contours:
    approx = cv2.approxPolyDP(cnt,0.01*cv2.arcLength(cnt,True),True)
    # print len(cnt)
    print len(approx)
    if len(approx) ==6 :
        print "Cube"
        cv2.drawContours(img,[cnt],-1,(255,0,0),3)
        cv2.putText(img,'Cube', pt ,cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 2, [0,255, 255], 2)
    elif len(approx) == 7:
        print "Cube"
        cv2.drawContours(img,[cnt],-1,(255,0,0),3)
        cv2.putText(img,'Cube', pt ,cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 2, [0, 255, 255], 2)
    elif len(approx) == 8:
        print "Cylinder"
        cv2.drawContours(img,[cnt],-1,(255,0,0),3)
        cv2.putText(img,'Cylinder', pt ,cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 2, [0, 255, 255], 2)
    elif len(approx) > 10:
        print "Sphere"
        cv2.drawContours(img,[cnt],-1,(255,0,0),3)
        cv2.putText(img,'Sphere', pt ,cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 2, [255, 0, 0], 2)

cv2.namedWindow("Shape", cv2.WINDOW_NORMAL)
cv2.imshow('Shape',img)

corners    = cv2.goodFeaturesToTrack(thresh_image,6,0.06,25)
corners    = np.float32(corners)
for    item in    corners:
    x,y    = item[0]
    cv2.circle(img,(x,y),10,255,-1)
cv2.namedWindow("Corners", cv2.WINDOW_NORMAL)
cv2.imshow("Corners",img)

cv2.waitKey()

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Segmentation Using Canny+Watershed in Opencv-python

Python Script is given below:

import cv2

# Importing opencv library
import numpy as np
#  Importing NumPy,which is the fundamental package for scientific computing with Python
img = cv2.imread('C:\\Users\Ram\Pictures\\humans\\368078.jpg')
# Read the image from disk
cv2.imshow("Original image", img)  # Display image
img_float = np.float32(img)  # Convert image from unsigned 8 bit to 32 bit float
criteria = (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 10, 1)
# Defining the criteria ( type, max_iter, epsilon )
# cv2.TERM_CRITERIA_EPS - stop the algorithm iteration if specified accuracy, epsilon, is reached.
# cv2.TERM_CRITERIA_MAX_ITER - stop the algorithm after the specified number of iterations, max_iter.
# cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER - stop the iteration when any of the above condition is met.
# max_iter - An integer specifying maximum number of iterations.In this case it is 10
# epsilon - Required accuracy.In this case it is 1
k = 50  # Number of clusters
ret, label, centers = cv2.kmeans(img_float, k, None, criteria, 50, cv2.KMEANS_RANDOM_CENTERS)
# apply kmeans algorithm with random centers approach
center = np.uint8(centers)
# Convert the image from float to unsigned integer
res = center[label.flatten()]
# This will flatten the label
res2 = res.reshape(img.shape)
# Reshape the image
cv2.imshow("K Means", res2)  # Display image
cv2.imwrite("1.jpg", res2)  # Write image onto disk
meanshift = cv2.pyrMeanShiftFiltering(img, sp=8, sr=16, maxLevel=1, termcrit=(cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 5, 1))
# Apply meanshift algorithm on to image
cv2.imshow("Output of meanshift", meanshift)
# Display image
cv2.imwrite("2.jpg", meanshift)
# Write image onto disk
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Convert image from RGB to GRAY
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
# apply thresholding to convert the image to binary
fg = cv2.erode(thresh, None, iterations=1)
# erode the image
bgt = cv2.dilate(thresh, None, iterations=1)
# Dilate the image
ret, bg = cv2.threshold(bgt, 1, 128, 1)
# Apply thresholding
marker = cv2.add(fg, bg)
# Add foreground and background
canny = cv2.Canny(marker, 110, 150)
# Apply canny edge detector
new, contours, hierarchy = cv2.findContours(canny, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# Finding the contors in the image using chain approximation
marker32 = np.int32(marker)
# converting the marker to float 32 bit
cv2.watershed(img,marker32)
# Apply watershed algorithm
m = cv2.convertScaleAbs(marker32)
ret, thresh = cv2.threshold(m, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
# Apply thresholding on the image to convert to binary image
thresh_inv = cv2.bitwise_not(thresh)
# Invert the thresh
res = cv2.bitwise_and(img, img, mask=thresh)
# Bitwise and with the image mask thresh
res3 = cv2.bitwise_and(img, img, mask=thresh_inv)
# Bitwise and the image with mask as threshold invert
res4 = cv2.addWeighted(res, 1, res3, 1, 0)
# Take the weighted average
final = cv2.drawContours(res4, contours, -1, (0, 255, 0), 1)
# Draw the contours on the image with green color and pixel width is 1
cv2.imshow("Watershed", final)  # Display the image
cv2.imwrite("3.jpg", final)  # Write the image
cv2.waitKey()  # Wait for key stroke

The result of the above script is given in the pdf below (2nd Answer):

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C Code to Perform Sampling Rate Convertion

  Sampling Rate Conversion in Real Time(Using a C language)

 

Upsampling and DownSampling using Reconstruction

(Using sinc Function):

Code:

#include<stdio.h>
#include<math.h>
#define PI 3.14
void main()
{
  int m,n,samplingrate,chunksize,subchunk2size,newchunksize,newsamplingrate,newsubchunk2size;
  float i;
  //int noofsamples;
  int factor;
  unsigned char a,b,c,d,e;
  FILE *fp,*fp2;
  void writeheaderfile(FILE *fp,int newsamplingrate,int newchunksize,int newsubchunk2size,FILE *fp2);
  void writedatafile(FILE *fp,int newsamplingrate,int newchunksize,int newsubchunk2size,float i,int subchunk2size,FILE *fp2);
  printf("Original Song is in : song1.wav\nResult is stored in : Createdsong.wav\n");
  fp=fopen("song1.wav","r");
  fp2=fopen("Createdsong.wav","w+");
  fseek(fp,24,SEEK_SET);
  fread(&samplingrate,4,1,fp);
  printf("Sampling Rate is : %d\n",samplingrate);
  fseek(fp,4,SEEK_SET);
  fread(&chunksize,4,1,fp);
  printf("chunksize is : %d\n",chunksize);
  fseek(fp,40,SEEK_SET);
  fread(&subchunk2size,4,1,fp);
  printf("subchunk2size is : %d\n",subchunk2size);
  printf("Enter the New Sampling Rate : ");scanf("%d",&newsamplingrate);
  i=(float)samplingrate/newsamplingrate;
  //printf("I value is : %f\n",i);
  //noofsamples=readnoofsamples(fp);
  printf("No of Samples in Given File : %d\n",subchunk2size/4);
  newsubchunk2size=subchunk2size/i;
  newchunksize=newsubchunk2size+36;
  //noofsamples=newsubchunk2size/4;
  writeheaderfile(fp,newsamplingrate,newchunksize,newsubchunk2size,fp2);
  //fclose(fp2);
 // fp2=fopen("Createdsong.wav","w+");
  writedatafile(fp,newsamplingrate,newchunksize,newsubchunk2size,i,subchunk2size,fp2);
}
/*int readnoofsamples(FILE *fp)
{
int count=1;
unsigned char c;
fp=fopen("song1.wav","r");
fseek(fp,44,SEEK_SET);
while(1)
{
if(feof(fp)) break;
fscanf(fp,"%c",&c);
count++;
//printf("%d\n",count);

}
//count=count/4;
return count;
}*/
void writedatafile(FILE *fp,int newsamplingrate,int newchunksize,int newsubchunk2size,float i,int subchunk2size,FILE *fp2)
{
//FILE *fp2;
int count=0,samco=1,center,samp=0,previous=0,x,temp;
short int e,r;
long int m,n,sumfr,sumfl;
float suml=0,sumr=0;
unsigned char z,s,v,w,c;
float sinc(int m,float i,int n);
printf("Writing the Samples in File....Please Wait....\n");
//fp=fopen("song1.wav","r");
fseek(fp,40,SEEK_SET);
    fread(&subchunk2size,4,1,fp);
    //printf("subchunk2size is : %d\n",subchunk2size);
    //fclose(fp);
//fp=fopen("song1.wav","r");
//fp2=fopen("Createdsong.wav","a");
fseek(fp,44,SEEK_SET);
fseek(fp2,44,SEEK_SET);
//printf("%d\n",subchunk2size);
for(m=0;m<=subchunk2size;m++)
{
//if(feof(fp)) break;

sumfl=0;
sumr=0;
suml=0;
sumfr=0;
center=rint(m*i);
if(previous==center)
{

}
else
{
for(temp=0;temp<(center-previous);temp++)
{
count++;
}
}
previous=center;
fseek(fp,44+(4*count),SEEK_SET);
for(n=count-10;n<count+10;n++)
{
//printf("m value : %d\n",m);
if(n<0)
{
e=0;
r=0;
}
else
{


fread(&e,2,1,fp);
fread(&r,2,1,fp);
}
sumr=sumr+(e*sinc(m,i,n));
suml=suml+(r*sinc(m,i,n));
sumfl=suml;
sumfr=sumr;
//if(sumfl==0) printf("m=%d\t n=%d\n",m,n);
//printf("m*I=%d\t n=%d\t e=%d\n",m*i,n,e);
//printf("suml=%lf\t sumr=%lf\t n=%d\t count=%d\t e=%d\t r=%d\n",suml,sumr,n,count,e,r);

}
fwrite(&sumfr,2,1,fp2);
fwrite(&sumfl,2,1,fp2);
/*fscanf(fp,"%c",&t);
fscanf(fp,"%c",&s);
fscanf(fp,"%c",&v);
fscanf(fp,"%c",&w);
printf("%d %d %d %d\n",t,s,v,w);*/
//if(sumfr==0) printf("m=%d\t and n=%d\n",m,n);
//printf("m=%d\t and sumfl=%d\t sumfr=%d\n",m,sumfl,sumfr);
//getchar();
}
printf("Process Completed...Result is in Createdsong.wav\n");

fclose(fp);
fclose(fp2);
}
float sinc(int m,float i,int n)
{
float temp;
if(rint(m*i)==n) 
{
//printf("sinc value is : %f\n",1.00);
return 1.00;
}
else
{
temp=PI*(m*i-n);
//printf("sinc value is : %f\n",(sin(temp)/temp));
return (sin(temp)/temp);
}
}

void writeheaderfile(FILE *fp,int newsamplingrate,int newchunksize,int newsubchunk2size,FILE *fp2)
{long int count=1;
unsigned char header;
//FILE *fp2;
//fp=fopen("song1.wav","r");
//fp2=fopen("Createdsong.wav","w+");
  fseek(fp,0,SEEK_SET);
  while(1)
 {
  fread(&header,4,1,fp);
  fwrite(&header,4,1,fp2);
  if(ftell(fp)==44) break;
 }
  fseek(fp2,4,SEEK_SET);
  fwrite(&newchunksize,4,1,fp2);
  fseek(fp2,24,SEEK_SET);
  fwrite(&newsamplingrate,4,1,fp2);
  fseek(fp2,40,SEEK_SET);
  fwrite(&newsubchunk2size,4,1,fp2);
  //fclose(fp2);
  //fclose(fp);
  //printf("Suc\n");
}

Down Sampling using Decimation(Without Using Sinc Function):

Code:

#include<stdio.h>
void main()
{
  FILE *fp,*fp2;
  unsigned char down;
  int samplingrate,ratio,i=4,chunksize,subchunk2size,newchunksize,newsubchunk2size;
  int newsamplingrate;
  long int count=1;
  
//Getting the Sampling Rate from the File 
  //  while(1)
 // {
    fp=fopen("mono.wav","r");
    fseek(fp,24,SEEK_SET);
    fread(&samplingrate,4,1,fp);
    rewind;
    fseek(fp,4,SEEK_SET);
    fread(&chunksize,4,1,fp);
    rewind;
    fseek(fp,40,SEEK_SET);
    fread(&subchunk2size,4,1,fp);
    
    //fscanf(fp,"%d",&sample);
    //**fprintf(stdout,"samplingrate is %u\n chunksize is : %u\nsubchunk2size is : %u\n",samplingrate,chunksize,subchunk2size);
    //count++;
    //if(count>44) break;
  //}
  //printf("The count value is : %ld\n",count-1);

fclose(fp);
//printf("Enter the New Sampling Rate : ");scanf("%d",&newsamplingrate);
newsamplingrate=5000;
if(newsamplingrate<samplingrate)
{  
  ratio=samplingrate/newsamplingrate;
  fp=fopen("song1.wav","r");
  fseek(fp,44,SEEK_SET);
  while(1)
  { 
    fscanf(fp,"%c",&down);
    //fprintf(stdout,"%d\t",down);
    count++;
    i--;
    if(feof(fp)) break;
    if(i<1)
    {
      i=4;
      fseek(fp,SEEK_CUR+4*(ratio-1)-1,SEEK_CUR);
    }   
  }


  fclose(fp);  

  count=count/4;
//  printf("Count is  : %ld\n",count);
  newsubchunk2size=chunksize/3;
  newchunksize=newsubchunk2size+36;
  writeheaderfile(fp,newsamplingrate,newchunksize,newsubchunk2size);
  writedatafile(fp,newsamplingrate,newchunksize,newsubchunk2size,ratio);

}
/*if(newsamplingrate>samplingrate)
{
  ratio=newsamplingrate/samplingrate;
  fp=fopen("song1.wav","r");
  fseek(fp,44,SEEK_SET);
  newsubchunk2size=chunksize*3;
  newchunksize=newsubchunk2size+36;
  writeheaderfile(fp,newsamplingrate,newchunksize,newsubchunk2size);
  writedataupfile(fp,newsamplingrate,newchunksize,newsubchunk2size,ratio);
}*/
}
//Writing the Header Section 
void writeheaderfile(FILE *fp,int newsamplingrate,int newchunksize,int newsubchunk2size)
{long int count=1;
unsigned char header;
FILE *fp2;
fp=fopen("mono.wav","r");
  fp2=fopen("song2.wav","w+");
  //rewind;
  while(1)
 {
  fread(&header,4,1,fp);
  //if(ftell(fp)==5) fprintf(fp2,"%c",newchunksize);
  //else if(ftell(fp)==17) fprintf(fp2,"%c",newsubchunk2size);
  //else if(ftell(fp)==25) fprintf(fp2,"%c",newsamplingrate);
  //else fprintf(fp2,"%c",header);
  fwrite(&header,4,1,fp2);
   if(ftell(fp)==44) {fclose(fp);break;}
 }
  //fp=fopen("song1.wav","r");
  //fp2=fopen("song2.wav","w+");
  //rewind(fp2);
  fseek(fp2,4,SEEK_SET);
  fwrite(&newchunksize,4,1,fp2);//fprintf(fp2,"%c",&newchunksize);
  //rewind(fp2);
  fseek(fp2,40,SEEK_SET);
  fwrite(&newsubchunk2size,4,1,fp2);
  //rewind(fp2);
  fseek(fp2,24,SEEK_SET);
  fwrite(&newsamplingrate,4,1,fp2);
  //fclose(fp);
  fclose(fp2);

  
}
//Write data to file
void writedatafile(FILE *fp,int newsamplingrate,int newchunksize,int newsubchunk2size,int ratio)
{unsigned char down;
 long int count=1;
 int i=4;
 FILE *fp2;
 fp=fopen("mono.wav","r");
 fp2=fopen("song2.wav","a+");
  fseek(fp,44,SEEK_SET);
  while(1)
  { 
    fscanf(fp,"%c",&down);
    fprintf(fp2,"%c",down);
    count++;
    i--;
    if(feof(fp)) break;
    if(i<1)
    {
      i=4;
      fseek(fp,SEEK_CUR+4*(ratio-1)-1,SEEK_CUR);
    }   
  }


  fclose(fp);  
  fclose(fp2);
}

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Transient Analysis of CMOS NAND gate

Transient analysis if a 2-input CMOS Nand gate is derived in the below pdf have a look at it .

 

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CMOS Buffer Using Two transistors

How to Analyse the Cmos Buffer With Two transistors

• This is one of the most prominent questions that is often asked in technical interviews of any electronics company.

• This circuit seems like it is very simple,but it if you start solving it it will lead to hell.

• In this post I will analyse this circuit and plot the VOUT vs VIN characteristics same as like the CMOS inverter.

I will give a few steps for users who are new.

• step1:

       Draw the Ids Vs vds Characteristics of PMOS.

• Step2:

       Draw the Ids Vs Vds charecteristics of NMOS.

• Step3:

       Overlap both the characteristics in a single plot.

• Step4:

       Find the Intersections Between the two plots for different values of Vgs.


These Values will give you the input and output values that are being satisfyied by the circuit.

As it is very tuff to say intutively that which transistor will On and which will off for which values of input because those conditions will include the output voltage,I use MATLAB to get these graphs and intersections.

The Matlab Code is given Below:

clc;
clear all;
close all; vdd=5; up=500; un=1500; cox=3.28e-6; wbyl=2; wbylp=6; vtn=0.5;
vtp=-0.5;
vin=0:0.1:5;
vout=0:0.01:5;
lengthofvin=length(vin); 
lengthofvout=length(vout);
for j=1:lengthofvin
for i=1:lengthofvout
if (vin(j)-vout(i)) < vtn currentn(j,i)=0;
end
if (vdd-vout(i))>(vin(j)-vout(i)-vtn)&& (vin(j)-vout(i))>=vtn
currentn(j,i)=0.5*un*cox*wbyl*((vin(j)-vout(i)-vtn).^2);
end
if (vdd-vout(i))<=(vin(j)-vout(i)-vtn )&& (vin(j)-vout(i))>=vtn
currentn(j,i)=un*cox*wbyl*(vin(j)-vout(i)-vtn-(vdd-vout(i))./2).*(vdd-vout(i));
end
end
end
for j=1:lengthofvin
for i=1:lengthofvout
if (vout(i)-vin(j)) < abs(vtp)
currentp(j,i)=0;
end
if (vout(i))>(vout(i)-vin(j)-abs(vtp))&& (vout(i)-vin(j))>=abs(vtp)
currentp(j,i)=0.5*up*cox*wbylp*((vout(i)-vin(j)-abs(vtp)).^2);
end
if (vout(i))<=(vout(i)-vin(j)-abs(vtp)) && (vout(i)-vin(j))>=abs(vtp)
currentp(j,i)=up*cox*wbylp*(vout(i)-vin(j)-abs(vtp)-((vout(i))./2))*(vout(i));
end
end
end
hold on; plot(vout,currentp','b');
xlabel('--------->vds'); 
ylabel('--------->ids');
title('Ids Vs Vds'); plot(vout,currentn','r'); hold off;
for j=1:lengthofvin
count=0;
for i=1:lengthofvout
if currentn(j,i)==currentp(j,i) 
newinput(1,j)=vin(j); 
if(vout(i)<=abs(vtp))
newoutput(1,j)=abs(vtp);
else if(vout(i)>=vdd-vtn)
newoutput(1,j)=vdd-vtn;
end newoutput(1,j)=vout(i); count=count+1;
if count==1 break;
end
end
end
end
end
for j=1:lengthofvin count=0;
for i=lengthofvout:-1:1
if currentn(j,i)==currentp(j,i)
newoutput1(j,1)=vout(i);
if(vout(i)>=vdd-vtn)
newoutput1(j,1)=vdd-vtn;
end 
count=count+1;
if count==1
break;
end
end
end
end
figure; hold on; 
plot(newinput,newoutput,'b',newinput,newoutput1,'b');
axis([0 5 0 5]);
xlabel('--------------->vin');
ylabel('--------------->vout'); 
title('Transfer Characteristics');

• The plot of the above MATLAB code will look something like give below:

                                           

                                                

                                     So in the graph you can see that the intersection of the PMOS and NMOS curves for a particular value of VGS are the input and output voltages that will satisfy this circuit conditions.And from the above plot it is clear that we can see a lot of intersections between the PMOS and NMOS curves .So let us consider the average value of voltage between the first point of intersection and the last point of intersection between the two PMOS and NMOS curves for a particular value of VGS. Then we will get the input versus output characteristics as shown below.But still we have a confusion because we took an average intersection point .

 

If we take the first intersection point ,then we will get the characteristics like shown below:

 

 

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