PROGRAM:
%PROGRAM for sine wave
t=0:0.1:10;
y=sin(2*pi*t);
subplot(3,3,1);
plot(t,y,'k');
xlabel('Time');
ylabel('Amplitude');
title('Sine wave');
%PROGRAM for cosine wave
t=0:0.1:10;
y=cos(2*pi*t);
subplot(3,3,2);
plot(t,y,'k');
xlabel('Time');
ylabel('Amplitude');
title('Cosine wave');
%PROGRAM for square wave
t=0:0.001:10;
y=square(t);
subplot(3,3,3);
plot(t,y,'k');
xlabel('Time');
ylabel('Amplitude');
title('Square wave');
%PROGRAM for sawtooth wave
t=0:0.1:10;
y=sawtooth(t);
subplot(3,3,4);
plot(t,y,'k');
xlabel('Time');
ylabel('Amplitude');
title('Sawtooth wave');
%PROGRAM for Triangular wave
t=0:.0001:20;
y=sawtooth(t,.5); % sawtooth with 50% duty cycle(triangular)
subplot(3,3,5);
plot(t,y);
ylabel ('Amplitude');
xlabel ('Time Index');
title('Triangular waveform');
%PROGRAM for Sinc Pulse
t=-10:.01:10;
y=sinc(t);
axis([-10 10 -2 2]);
subplot(3,3,6)
plot(t,y)
ylabel ('Amplitude');
xlabel ('Time Index');
title('Sinc Pulse');
% PROGRAM for Exponential Growing signal
t=0:.1:8;
a=2;
y=exp(a*t);
subplot(3,3,7);
plot(t,y);
ylabel ('Amplitude');
xlabel ('Time Index'); title('Exponential growing Signal');
% PROGRAM for Exponential Growing signal t=0:.1:8;
a=2;
y=exp(-a*t); subplot(3,3,8); plot(t,y);
ylabel ('Amplitude');
xlabel ('Time Index');
title('Exponential decaying Signal');
OUTPUT:
PROGRAM:
%PROGRAM for unit step sequence
clc;
N=input('Enter the length of unit step sequence(N)= ');
n=0:1:N-1;
y=ones(1,N);
subplot(3,2,1);
stem(n,y,'k');
xlabel('Time')
ylabel('Amplitude')
title('Unit step sequence');
%PROGRAM for unit ramp sequence
N1=input('Enter the length of unit ramp sequence(N1)= ');
n1=0:1:N1-1;
y1=n1;
subplot(3,2,2);
stem(n1,y1,'k');
xlabel('Time');
ylabel('Amplitude');
title('Unit ramp sequence');
%PROGRAM for sinusoidal sequence
N2=input('Enter the length of sinusoidal sequence(N2)=');
n2=0:0.1:N2-1;
y2=sin(2*pi*n2);
subplot(3,2,3);
stem(n2,y2,'k');
xlabel('Time');
ylabel('Amplitude');
title('Sinusoidal sequence');
%PROGRAM for cosine sequence
N3=input('Enter the length of the cosine sequence(N3)=');
n3=0:0.1:N3-1;
y3=cos(2*pi*n3);
subplot(3,2,4);
stem(n3,y3,'k');
xlabel('Time');
ylabel('Amplitude');
title('Cosine sequence');
%PROGRAM for exponential sequence
N4=input('Enter the length of the exponential sequence(N4)= ');
n4=0:1:N4-1;
a=input ('Enter the value of the exponential sequence(a)= ');
y4=exp (a*n4);
subplot(3,2,5);
stem(n4,y4,'k');
xlabel('Time');
ylabel('Amplitude');
title('Exponential sequence');
%PROGRAM for unit impulse
n=-3:1:3;
y=[zeros(1,3),ones(1,1),zeros(1,3)];
subplot(3,2,6);
stem(n,y,'k');
xlabel('Time');
ylabel('Amplitude ');
title('Unit impul sequence');
OUTPUT:
PROGRAM:
clc;
clear all;
close all;
x=input('Enter the sequence 1: ');
h=input('Enter the sequence 2: ');
y=xcorr(x,h);
figure;
subplot(3,1,1);
stem(x);
xlabel('n->');
ylabel('Amplitude->');
title('Input sequence 1');
subplot(3,1,2);
stem(fliplr(y));
stem(h);
xlabel('n->');
ylabel('Amplitude->');
title('Input sequence 2');
subplot(3,1,3);
stem(fliplr(y));
xlabel('n->');
ylabel('Amplitude->');
title('Output sequence');
disp('The resultant is');
fliplr(y);
OUTPUT:
(Cross-Correlation of the Sequences)
Enter the sequence 1: [1 3 5 7]
Enter the sequence 2: [2 4 6 8]
(Auto Correlation Function)
Enter the sequence [1 2 3 4]
PROGRAM:
clc;
close all;
clear all;
x=input('Enter x: ');
h=input('Enter h: ') ;
m=length(x);
n=length(h);
X=[x,zeros(1,n)];
H=[h,zeros(1,m)];
for i=1:n+m-1
Y(i)=0;
for j=1:i
Y(i)=Y(i)+X(j)*H(i-j+1);
end
end
stem(Y);
disp(Y);
ylabel('Y[n]');
xlabel('----->n') ;
title('Convolutio n of Two Signals without conv function');
INPUT:
Enter x: [1 2 3 4 5]
x=12345
Enter h: [1 2 3 1]
h=1231
Y = 1 4 10 17 24 25 19 5
OUTPUT:
PROGRAM:
clc;
clear all ;
close all;
a = input('Enter the sequence x(n) = ');
b = input('Enter the sequence h(n) = ');
n1=length(a);
n2=length(b);
N=max(n1,n2);
x = [a zeros(1,(N-1))];
for i = 1:N
k = i;
for j = 1:n2
H(i,j)=x(k)*b(j);
k = k-1;
if(k == 0)
k = N;
end
end
end
y=zeros(1,N);
M=H';
for j = 1:N
for i = 1:n2
y(j)=M(i,j)+y(j);
end
end
disp('The output sequence is y(n)=');
disp(y);
stem(y);
title('Circular Convolution');
xlabel('n');
ylabel('y(n)');
INPUT:
Enter the sequence x(n) = [1 2 3 4]
x(n) = 1 2 3 4
Enter the sequence h(n) = [1 2 1 1]
h(n) = 1 2 1 1
The output sequence is y(n)=
14 11 12 13
OUTPUT:
PROGRAM : (Spectrum Analysis Using DFT)
clc;
clear all ;
close all;
N=input('type length of DFT= ');
T=input('type sampling period= ');
freq=input('type the sinusoidal freq= ');
k=0:N-1;
f=sin(2*pi*freq*1/T*k);
F=fft(f);
stem(k,abs(F));
grid on;
xlabel('k');
ylabel('X(k)');
Output:
(Spectrum Analysis Using DFT)
Type length of dft=32
Type sampling period=64
Type the sinusoidal freq=11
PROGRAM : (Rectangular Window)
clc;
clear all ;
close all;
rp=input('Enter the PB ripple rp =');
rs=input('Enter the SB ripple rs =');
fp=input('Enter the PB ripple fp =');
fs=input('Enter the SB ripple fs =');
f=input('Enter the sampling frequency f =');
wp=2*fp/f;
ws=2*fs/f;
num=-20*log10(sqrt(rp*rs))-13;
den=14.6*(fs-fp)/f;
n=ceil(num/den);
n1=n+1;
if(rem(n,2)~=0)
n=n1;
n=n-1;
end;
y=boxcar(n1);
%LPF
b=fir1(n,wp,y);
[h,o]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,1);
plot(o/pi,m);
xlabel('Normalized frequency------>'); ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF LPF');
%HPF
b=fir1(n,wp,'high',y);
[h,o]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,2);
plot(o/pi,m);
xlabel('Normalized frequency------>');
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF HPF');
%BPF
wn=[wp ws];
b=fir1(n,wn,y);
[h,o]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,3);
plot(o/pi,m);
xlabel('Normalized frequency------>');
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF BPF');
%BSF
b=fir1(n,wn,'stop',y);
[h,o]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,4);
plot(o/pi,m);
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF LPF');
%HPF
b=fir1(n,wp,'high',y);
[h,o]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,2);
plot(o/pi,m);
xlabel('Normalized frequency------>');
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF HPF');
%BPF
wn=[wp ws];
b=fir1(n,wn,y);
[h,o]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,3);
plot(o/pi,m);
xlabel('Normalized frequency------>');
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF BPF');
%BSF
b=fir1(n,wn,'stop',y);
[h,o]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,4);
plot(o/pi,m);
xlabel('Normalized frequency------
>');
ylabel('Gain
in db--------.');
title('MAGNITUDE RESPONSE OF BSF');
Output:
Enter the PB ripple Rp =.03
Enter the SB ripple rs =.05
Enter the PB ripple fp =2000
Enter the SB ripple fs =3000
Enter the Sampling frequency f =9000
PROGRAM : (Rectangular Window)
clc;
clear all ;
close all;
rp=input('Enter the PB ripple rp =');
rs=input('Enter the SB ripple rs =');
fp=input('Enter the PB ripple fp =');
fs=input('Enter the SB ripple fs =');
f=input('Enter the sampling frequency f =');
wp=2*fp/f;
ws=2*fs/f;
num=-20*log10(sqrt(rp*rs))-13;
den=14.6*(fs-fp)/f;
n=ceil(num/den);
n1=n+1;
if(rem(n,2)~=0)
n=n1;
n=n-1;
end;
y=hanning(n1);
%LPF
b=fir1(n,wp,y);
[h,O]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,1);
plot(O/pi,m);
xlabel('Normalized freqency------>');
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF LPF');
%HPF
b=fir1(n,wp,'high',y);
[h,O]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,2);
plot(O/pi,m);
xlabel('Normalized freqency------>');
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF HPF');
%BPF
wn=[wp ws];
b=fir1(n,wn,y);
[h,O]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,3);
plot(O/pi,m);
xlabel('Normalized freqency------>');
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF BPF');
%BSF
b=fir1(n,wn,'stop',y);
[h,O]=freqz(b,1,256);
m=20*log10(abs(h));
subplot(2,2,4);
plot(O/pi,m);
xlabel('Normalized freqency------>');
ylabel('Gain in db--------.');
title('MAGNITUDE RESPONSE OF BSF');
Output(Hanning Window)
Enter the PB ripple rP =.03
Enter the SB ripple rs=.02
Enter the PB ripple fp =1500
Enter the SB ripple fs =2000
Enter the Sampling frequency f =9000
PROGRAM : (IIR Butterworth Filter using Impulse Method)
clc;
clear all ;
close all;
N=input('ENTER THE FILTER ORDER N = ');
fs=input('ENTER THE SAMPLING FREQUENCY fs = ');
fc=input('ENTER THE CUT-OFF FREQUENCY fc = ');
wc=2*pi*fc;
[na,da]=butter(N,wc,'s');
[n,d]=impinvar(na,da,fs);
[h,f]=freqz(n,d,512,fs);
gain=20*log10(abs(h));
subplot(2,1,1);
plot(f,gain);
xlabel('Frequency---->');
ylabel('Magnitude---->');
title('AMPLITUDE RESPONSSE');
subplot(2,1,2);
zplane(n,d);
z=roots(n); p=roots(d);
xlabel('Real part---->');
ylabel('Imaginary part---->');
title('POLE-ZERO PLOT');
Output: (IIR Butterworth Filter using Impulse Method)
Enter the filter order N = 2
Enter the Sampling Frequency fs =12800
Enter the cut off frequency fc = 150
PROGRAM : (IIR Butterworth Filter using Bilinear Transformation)
clc;
clear all ;
close all;
wp=input('ENTER THE PASSBAND EDGE FREQUENCIES wp= ');
ws=input('ENTER THE STOPBAND EDGE FREQUENCIES ws= ');
rp=input('ENTER THE PASSBAND RIPPLE rp= ');
rs=input('ENTER THE STOPBAND RIPPLE rs= ');
fs=input('ENTER THE SAMPLING FREQUENCY fs= ');
wpn=wp/(fs/2);
wsn=ws/(fs/2);
[N,fc]=buttord(wpn,wsn,rp,rs);
disp('ORDER OF THE FILTER');
disp(N);
[n,d]=butter(N,wpn);
[h,f]=freqz(n,d,512,fs);
gain=20*log10(abs(h));
an=angle(h);
subplot(2,1,1);
plot(f,gain);
xlabel('FREQUENCY---->');
ylabel('MAGNITUDE');
title('AMPLITUDE RESPONSE');
subplot(2,1,2);
zplane(n,d);
z=roots(n);
p=roots(d);
xlabel('RREAL PART---->');
ylabel('IMAGINARY PART');
title('POLE-ZERO PLOT');
Input: (IIR Butterworth Using Bilinear Transformation)
Enter the passband edge frequencies wp= [200 300]
Enter the stopband edge frequencies ws= [50 450]
Enter the passband ripple rp= 3
Enter the stopband ripple rs= 20
Enter the sampling frequency fs= 1000
Order of the filter = 2
Output:
PROGRAM : (Chebyshev Type 1 Band pass Filter)
clc;
clear all ;
close all;
alphap=2; %pass band attenuation in dB
alphas=20; %stop band attenuation in dB
wp=[.2*pi,.4*pi];
ws=[.1*pi,.5*pi];
%To find cutoff frequency and order of the filter
[n,wn]=buttord(wp/pi,ws/pi,alphap,alphas);
%system function of the filter
[b,a]=cheby1(n,alphap,wn); w=0:.01:pi;
[h,ph]=freqz(b,a,w);
m=20*log10(abs(h));
an=angle(h);
subplot(2,1,1);
plot(ph/pi,m);
grid;
ylabel('Gain in dB..');
xlabel('Normalised frequency..');
subplot(2,1,2);
plot(ph/pi,an);
grid;
ylabel('Phase in radians..');
xlabel('Normalised frequency..');
Output: (Chebyshev Type 1 Band pass Filter)
PROGRAM : (Chebyshev Type II Band Reject Filter)
clc;
clear all ;
close all;
alphap=2;
alphas=20;
ws=[.2*pi,.4*pi];
wp=[.1*pi,.5*pi];
[n,wn]=cheb2ord(wp/pi,ws/pi,alphap,alphas);
[b,a]=cheby2(n,alphas,wn,'stop');
w=0:.01:pi;
[h,ph]=freqz(b,a,w);
m=20*log10(abs(h));
an=angle(h);
subplot(2,1,1);
plot(ph/pi,m);
grid;
ylabel('Gain in dB..');
xlabel('Normalised frequency..');
subplot(2,1,2);
plot(ph/pi,an);
grid;
ylabel('Phase in radians..');
xlabel('Normalised frequency..');
Output: (Chebyshev Type II Band Reject Filter)
PROGRAM : (Multirate Filters)
clc;
clear all ;
close all;
N =31; % Filter length
Nord = N-1; % Filter order
L = 3;
ro1 = 0.2; % Roll-off factor
h1 = firnyquist(Nord,L,ro1); % Filter design
ro2 = 0.4; % Roll-off factor
h2 = firnyquist(Nord,L,ro2); % Filter design
ro3 = 0.6; % Roll-off factor
h3 = firnyquist(Nord,L,ro3); % filter design
figure (1)
subplot(3,1,1)
stem(0:N-1,h1,'b')
axis([0,30,-0.2,0.5])
ylabel('h_1[n]')
title('Figure 1')
legend('h1')
subplot(3,1,2)
stem(0:N-1,h2,'k')
axis([0,30,-0.2,0.5])
ylabel('h_2[n]')
legend('h2')
subplot(3,1,3)
stem(0:N-1,h3,'r')
axis([0,30,-0.2,0.5])
xlabel('n')
ylabel('h_3[n]')
legend('h3')
% Computing frequency responses
[H1,f] = freqz(h1,1,256,2);
[H2,f] = freqz(h2,1,256,2);
[H3,f] = freqz(h3,1,256,2); figure (2)
plot(f,abs(H1),'b',f,abs(H2),'k',f,abs(H3),'r'),
grid title ('Figure 2')
axis([0,1,0,1.1])
xlabel('\omega/\pi')
ylabel('Magnitude')
legend('|H_1(e^j^\omega)|','|H_2(e^j^\omega)|','|H_3(e^j^ \omega)|')
Output:
PROGRAM : (Multirate Filters)
clc;
clear all ;
close all;
M=3000;
T=2000;
dB=25;
L=20;
ChL=5;
EqD=round((L+ChL)/2);
Ch=randn(1,ChL+1)+sqrt(-1)*randn(1,ChL+1);
Ch=Ch/norm(Ch);
TxS=round(rand(1,M))*2-1;
TxS=TxS+sqrt(-1)*(round(rand(1,M))*2-1);
x=filter(Ch,1,TxS);
n=randn(1,M);
n=n/norm(n)*10^(-dB/20)*norm(x);
x=x+n; K=M-L;
X=zeros(L+1,K);
for i=1:K
X(:,i)=x(i+L:-1:i).';
end
e=zeros(1,T-10);
c=zeros(L+1,1);
mu=0.001;
for i=1:T-10
e(i)=TxS(i+10+L-EqD)-c'*X(:,i+10);
c=c+mu*conj(e(i))*X(:,i+10);
end
sb=c'*X;
sb1=sb/norm(c);
sb1=sign(real(sb1))+sqrt(-1)*sign(imag(sb1));
start=7;
sb2=sb1-TxS(start+1:start+length(sb1));
SER=length(find(sb2~=0))/length(sb2);
disp(SER);
subplot(2,2,1),
plot(TxS,'*');
grid,title('Input symbols'); xlabel('realpart'),
ylabel('imaginary part')
axis([-2 2 -2 2])
subplot(2,2,2),
plot(x,'o');
grid, title('Received samples'); xlabel('real part'),
ylabel('imaginary part')
subplot(2,2,3),
plot(sb,'o');
grid, title('Equalized symbols'),
xlabel('real part'),
ylabel('imaginary part')
subplot(2,2,4),
plot(abs(e));
grid, title('Convergence'),
xlabel('n'),
ylabel('error signal')
Output:
PROGRAM (Linear Convolution)
#include<stdio.h>
int m=6;
int n=6;
int i=0,j;
int x[15]={1,2,3,4,5,6,0,0,0,0,0,0}; int h[15]={1,2,3,4,5,6,0,0,0,0,0,0};
int y[20];
main()
{
for(i=0;i<m+n-1;i++)
{
y[i]=0;
for(j=0;j<=i;j++)
y[i]+=x[j]*h[i-j];
}
for(i=0;i<m+n-1;i++)
printf("%d \n",y[i]);
}
OUTPUT: (Linear Convolution)
4 10 20 35 56 70 76 73 60 36
PROGRAM :(Circular Convolution)
#include<stdio.h>
int
m,n,x[30],h[30],y[30],i,j,temp[30],k,x2[30],a[30];
void main()
{
printf("enter the length of the 1st sequence\n");
scanf("%d",&m);
printf("enter the length of the second sequence\n"); scanf("%d",&n);
printf("enter the 1st sequence\n");
for(i=0;i<m;i++)
scanf("%d",&x[i]);
printf("enter the second sequence\n");
for(j=0;j<n;j++)
scanf("%d",&h[j]);
if(m-n!=0)
{
if(m>n)
{
for(i=n;i<m;i++)
h[i]=0;
n=m;
}
for(i=m;i<n;i++)
x[i]=0;
m=n;
}
y[0]=0;
a[0]=h[0];
for(j=1;j<n;j++)
a[j]=h[n-j];
for(i=0;i<n;i++)
y[0]+=x[i]*a[i];
for(k=1;k<n;k++)
{
y[k]=0;
for(j=1;j<n;j++)
x2[j]=a[j-1];
x2[0]=a[n-1];
for(i=0;i<n;i++)
{
a[i]=x2[i];
y[k]+=x[i]*x2[i];
}
}
printf("the circular convolution is\n");
for(i=0;i<n;i++)
printf("%d\t",y[i]);
}
INPUT: (Circular Convolution)
Enter the length of the 1st sequence 5
Enter the length of the second sequence 5
Enter the 1st sequence 1 2 3 4 5
Enter the second sequence 1 2 3 4 5
OUTPUT:
The circular convolution is
45 50 50 45 35
PROGRAM: (FFT Implementation)
#include<stdio.h>
#include<math.h>
#define N 8
#define PI 3.14159
typedef struct
{
float real,imag;
}
complex;
main()
{
int i;
complex w[N];
complex
x[8]={0,0.0,1,0.0,2,0.0,3,0.0,4,0.0,5,0.0,6,0.0,7,0.0}; complex temp1,temp2;
int j,k,upper_leg,lower_leg,leg_diff,index,step;
for(i=0;i<N;i++)
{
w[i].real=cos((2*PI*i)/(N*2.0));
w[i].imag=-sin((2*PI*i)/(N*2.0));
}
leg_diff=N/2;
step=2;
for(i=0;i<3;i++)
{
index=0;
for(j=0;j<leg_diff;j++)
{
for(upper_leg=j;upper_leg<N;upper_leg+=(2*leg_diff))
{
lower_leg=upper_leg+leg_diff;
temp1.real=(x[upper_leg]).real+(x[lower_leg]).real;
temp1.imag=(x[upper_leg]).imag+(x[lower_leg]).imag;
temp2.real=(x[upper_leg]).real-(x[lower_leg]).real;
temp2.imag=(x[upper_leg]).imag-(x[lower_leg]).imag;
(x[lower_leg]).real=temp2.real*(w[index]).real-
temp2.imag*(w[index]).imag;
(x[lower_leg]).imag=temp2.real*(w[index]).imag+temp2.imag
*(w[index]).real;
(x[upper_leg]).real=temp1.real;
(x[upper_leg]).imag=temp1.imag;
}
index+=step;
}
leg_diff=(leg_diff)/2;
step=step*2;
}
j=0;
for(i=1;i<(N-1);i++)
k=N/2;
while(k<=j)
{
j=j-k;
k=k/2;
}
j=j+k;
if(i<j)
{
temp1.real=(x[j]).real;
temp1.imag=(x[j]).imag;
(x[j]).real=(x[i]).real;
(x[j]).imag=(x[i]).imag;
(x[i]).real=temp1.real;
(x[i]).imag=temp1.imag;
}
}
printf("the fft of the given input sequence is \n");
for(i=0;i<8;i++)
{
printf("%f %f \n",(x[i]).real,(x[i]).imag);
}
}
OUTPUT: (FFT Implementation)
The FFT of the given input sequence is:
28.000000 0.000000
-4.000012 9.656858
-4.000005 4.000000
-4.000010 1.656851
-4.000000 0.000000
-3.999998 -1.656858
-3.999995 -4.000000
-3.999980 -9.656851
PROGRAM: (Sine waveform)
#include <stdio.h>
#include <math.h>
float a[500];
void main()
{
int i=0;
for(i=0;i<500;i++)
{
a[i]=sin(2*3.14*10000*i);
}
}
OUTPUT: ( Sine waveform)
PROGRAM: ( Square waveform)
#include <stdio.h>
#include <math.h>
int a[1000];
void main()
{
int i,j=0;
int b=5;
for(i=0;i<10;i++)
{
for (j=0;j<=50;j++)
{
a[(50*i)+j]=b;
}
b=b*(-1) ;
}
}
OUTPUT: ( Square waveform)
PROGRAM: (FIR Filters)
#include<stdio.h>
#include<math.h>
#define pi 3.1415
int n,N,c;
float wr[64],wt[64];
void main()
{
printf("\n enter no. of samples,N= :"); scanf("%d",&N);
printf("\n enter choice of window function\n 1.rect
\n 2. triang \n c= :");
scanf("%d",&c);
printf("\n elements of window function are:"); switch(c)
{
case 1:
for(n=0;n<=N-1;n++)
{
wr[n]=1;
printf(" \n wr[%d]=%f",n,wr[n]);
}
break;
case 2:
for(n=0;n<=N-1;n++)
{
wt[n]=1-(2*(float)n/(N-1));
printf("\n wt[%d]=%f",n,wt[n]);
}
break;
}
}
OUTPUT: (FIR Filters)
PROGRAM: (IIR Filters)
#include<stdio.h>
#include<math.h>
int i,w,wc,c,N;
float H[100];
float mul(float,int);
void main()
{
printf("\n Enter order of filter"); scanf("%d",&N);
printf("\n Enter the cut off frequency"); scanf("%d",&wc);
printf("\n Enter the choice for IIR Filter 1.LPF 2.HPF");
scanf("%d",&c);
switch(c)
{
case 1:
for(w=0;w<100;w++)
{
H[w]=1/sqrt(1+mul((w/(float)wc),2*N));
printf("H[%d]=%f\n",w,H[w]);
}
break;
case 2:
for(w=0;w<=100;w++)
{
H[w]=1/sqrt(1+mul((float)wc/w,2*N));
printf("H[%d]=%f\n",w,H[w]);
}
break;
}
}
float mul(float a,int x)
{
for(i=0;i<x-1;i++)
a*=a;
return(a); }
INPUT: (IIR Filters)
Enter order of filter
2
Enter the cut off frequency
50
Enter the choice for IIR Filter 1.LPF 2.HPF:
OUTPUT: (IIR Filters)
PROGRAM :
function ADCNoiseGain=ADCNoise(b,a,n,FM)
[B,A] = sos2tf([b a]); %form A(z) and B(z)
[h,t] = impz(B,A,n);
ADCNoiseGain = sum(h.^2)/12.0;
fprintf('ADC noise gain is %f\n\n',ADCNoiseGain); if FM~=1
fprintf('ADC noise is %g^2*%g*q^2\n',[FM ADCNoiseGain]); else
fprintf('ADC noise is %g*q^2\n',ADCNoiseGain); end
function CoeffQuantizeErr(b,a,maxbits,ftype,f,Fs)
%COEFFICIENT QUANTIZATION ERROR ANALYSIS
n=256;
for nbits=2:maxbits [B,A]=QuantizeCoeff(b,a,nbits); [B,A] = sos2tf([B A]);
[h,w] = freqz(B,A,n);
amag = abs(h);
amag = amag/max(amag); response
dev(nbits-1,:) = RippleAtten(ftype,f,amag,n,Fs); fprintf('nbits\tband1\t\tband2\t\tband3\n');
fprintf('%d\t%f\t%f\t%f\n',reshape([(2:maxbits)' dev]',maxbits-1,4));
fprintf('\nfrequency response with quantization noise for desired wordlength:\n');
bits=input('wordlength(32 for unquantized coefficients): ');
[B,A] = sos2tf([b a]);
freqz(B,A,n);
hold on;
[B,A] = QuantizeCoeff(b,a,nbits);
[B,A] = sos2tf([B A])
freqz(B,A,n);
title('Frequency Response for Desired Wordlength');
function Stability(b,a,maxbits) format long;
fprintf('\n\nnbits\tstage\tA1\tA2\tradius1\tangle1\tradiu
s2\tangle2\n');
for nbits=2:maxbits
[B,A]=QuantizeCoeff(b,a,nbits);
for i=1:size(b,1)
r1 = sqrt(abs(A(i,3)));
angle1 = 180/pi*acos(A(i,2)/(-2.0*r1)); r2 = sqrt(abs(a(i,3)));
angle2 = 180/pi*acos(a(i,2)/(-2.0*r2)); fprintf('%d\t%d\t%-7.4f\t%-7.4f\t%-7.4f\t%-7.2f\t%-
7.4f\t%-7.2f\n',nbits,i,A(i,2),A(i,3),r1,angle1,r2,angle2);
end
end
format;
function ScaleFactor(b,a,nstep,size,structure)
norm0 = DirectScale(b,a,0,nstep);
norm1 = DirectScale(b,a,1,nstep); norm2 = DirectScale(b,a,2,size); else
norm0 = CanonicScale(b,a,0,nstep);
norm1 = CanonicScale(b,a,1,nstep);
norm2 = CanonicScale(b,a,2,size);
end
disp('L1-norms of the second order sections:'); disp(norm0); disp('L2-norms of the second
order sections:'); disp(norm1); disp('Loo-norms of the second order sections:');disp(norm2);
function s = DirectScale(b,a,iopt,n)
if(iopt>=3)
s = ones(1,size(b,1));
return;
else
A = 1; B = 1;
for i=1:size(b,1) %loop for each stage A = conv(A,a(i,:));
B = conv(B,b(i,:));
s(i) = GetScaleFactor(B,A,iopt,n);
end
end
function s = CanonicScale(b,a,iopt,n)
if(iopt>=3)
s = ones(1,size(b,1));
return;
else
A = 1; B = 1;
for i=1:size(b,1)
A = conv(A,a(i,:));
if i>1
B = conv(B,b(i-1,:));
end
s(i) = GetScaleFactor(B,A,iopt,n); end end
ylabel('error signal')
