% Integration approximation and Signal energy and power:
%
% @ Kefu Xue, Ph.D., June 2006
%
% Energy calucation for an exponential signal:
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T=10^-3; % pick a sampling frequency (the smaller T the better approximation)
D=100; % pickup a duration of 100 seconds
N=D/T; % total number of samples
t=[0:N-1]*T;
xe=3*exp(-2*t);
Exe=sum(xe.*xe)*T;
disp(['The approximated total energy is ' num2str(Exe)]);
%
% Power calculation:
% 
f0=20; % fundamental frequency from Maximum Common Factor: 40pi
T0=1/f0; % shortest period of the signal
T=T0/40; % sampling 40 samples over a period of the signal
N=120; % plot 3 periods
t=[0:N-1]*T; % time sampling vector
s1=2*cos(200*pi*t-1);
Ps1=sum(s1(1:40).^2)/40;
display(['The power of a sinusoidal s1 (A^2/2) is equal to ' num2str(Ps1)]);
s2=sin(120*pi*t+pi/3);
Ps2=sum(s2(1:40).^2)/40;
display(['The power of a sinusoidal s2 is equal to ' num2str(Ps2)]);
s3=-0.5*cos(80*pi*t+2);
Ps3=sum(s3(1:40).^2)/40;
display(['The power of a sinusoidal s3 is equal to ' num2str(Ps3)]);
x=s1+s2+s3;
Px=sum(x(1:40).^2)/40;
display(['The power of multiple sinusoids is equal to ' num2str(Px)]);
%
% end of file