MATLAB and C Programs - Digital Signal Processing: A Practitioner's Approach - page 135

subplot(222);plot(f1,M(1:n),f1,mark(1:n));grid;title('B')
ylabel(' Power Spectrum ');
%title ( ' Fourier transform of R(tow) ')
%title ( ' Fig 2.5 ')
%print -depsc f2_5;pause;
subplot(221);plot(T,Rtow);grid;title('A')
ylabel(' Auto Correlation ');
%title ( ' Auto Correlation function R(tow) ');
%title ( ' Fig 2.4 ');
print -depsc f2_4;pause
td=td-1;
%subplot(211) ;plot(tc,y) ;grid
%subplot(212) ;plot(td,y1,td,y2);grid;pause;
%subplot(211);plot(td(1:60),y2(1:60),td(1:60),y2(1:60),'o');grid
subplot(211);stem(td(1:30), y2(1:30));grid
ylabel(' Impulse Response ');xlabel(' Time ')
%title('Fig 2.3');
print -depsc f2_3
A.2.2 Program f 2_7
%Digital Signal Processing:A Practitioner's Approach
%Dr.Kaluri Venkata Ranga Rao, [e-mail]
%Generates figure 2.6
clear;close;
delta=0.1;
f=100;
omega=2*pi*f;
b1=omega*omega;
a1=[1 2*delta*omega omega*omega];
sysc=tf(b1,a1);
Ts1=1/(4*f);
Ts2=1/(50*f);
imax=10;
Ts3=linspace(Ts1,Ts2,imax);
for i=1:imax
Ts=Ts3(i);
sysd=c2d(sysc,Ts,'tustin');
[b a]=tfdata(sysd,'v');
q=abs(roots(a));
g1(i)=b(1);
r1(i)=q(1);