filtdem.m

matlabDigitalSigalProcess内有文件若干

function slide=filtdem
% FILTDEM  Filter design and filtering demo.
%   This demonstration designs a filter with the Signal Processing Toolbox
%   and applies it to a signal made up of harmonic components.  
%
%   To see it run, type 'filtdem'. 
%
%   See also FILTDEM2, FILTDEMO.

%   Copyright (c) 1988-98 by The MathWorks, Inc.
% $Revision: 5.9 $

if nargout<1,
  playshow filtdem
else
  %========== Slide 1 ==========

  slide(1).code={
   'Fs=100;',
   't=(1:100)/Fs;',
   's1=sin(2*pi*t*5); s2=sin(2*pi*t*15); s3=sin(2*pi*t*30);',
   '   s=s1+s2+s3;',
   '    plot(t,s);',
   '    xlabel(''Time (seconds)'');',
   '    ylabel(''Time waveform'');',
   '    drawnow;',
   '' };
  slide(1).text={
   ' Press the "Start" button to see a demonstration of',
   ' filtering with the Signal Processing Toolbox.',
   '',
   ' >> Fs=100;',
   ' >> t=(1:100)/Fs;',
   ' >> s1=sin(2*pi*t*5); s2=sin(2*pi*t*15); s3=sin(2*pi*t*30);',
   ' >> s=s1+s2+s3;',
   ' >> plot(t,s);'};

  %========== Slide 2 ==========

  slide(2).code={
};
  slide(2).text={
   ' Here''s an example of filtering with the Signal Processing',
   ' Toolbox.  First make a signal with three sinusoidal',
   ' components (at frequencies of 5, 15, and 30 Hz).',
   ' >> Fs=100;',
   ' >> t=(1:100)/Fs;',
   ' >> s1=sin(2*pi*t*5); s2=sin(2*pi*t*15); s3=sin(2*pi*t*30);',
   ' >> s=s1+s2+s3;',
   ' >> plot(t,s);'};

  %========== Slide 3 ==========

  slide(3).code={
   '[b,a]=ellip(4,0.1,40,[10 20]*2/Fs);',
   '[H,w]=freqz(b,a,512);',
   'plot(w*Fs/(2*pi),abs(H));',
   'xlabel(''Frequency (Hz)'');',
   'ylabel(''Mag. of frequency response'');',
   'grid;',
   'drawnow;',
   '' };
  slide(3).text={
   ' To design a filter to keep the 15 Hz sinusoid and get rid',
   ' of the 5 and 30 Hz sinusoids, we create an eighth order',
   ' IIR filter with a passband from 10 to 20 Hz.  Here is its',
   ' frequency response. The filter was created with the ELLIP',
   ' command.',
   ' >> [b,a]=ellip(4,0.1,40,[10 20]*2/Fs);',
   ' >> [H,w]=freqz(b,a,512);',
   ' >> plot(w*Fs/(2*pi),abs(H));'};

  %========== Slide 4 ==========

  slide(4).code={
   'sf=filter(b,a,s);',
   'plot(t,sf);',
   'xlabel(''Time (seconds)'');',
   'ylabel(''Time waveform'');',
   'axis([0 1 -1 1]);',
   'drawnow; pause(1);' };
  slide(4).text={
   'After filtering, we see the signal is a 15 Hz sinusoid,',
   ' exactly as expected.',
   '',
   ' >> sf=filter(b,a,s);',
   ' >> plot(t,sf);',
   ' >> xlabel(''Time (seconds)'');',
   ' >> ylabel(''Time waveform'');',
   ' >> axis([0 1 -1 1]);'};

  %========== Slide 5 ==========

  slide(5).code={
   'S=fft(s,512);',
   'SF=fft(sf,512);',
   'w=(0:255)/256*(Fs/2);',
   'plot(w,abs([S(1:256)'' SF(1:256)'']));',
   'xlabel(''Frequency (Hz)'');',
   'ylabel(''Mag. of Fourier transform'');',
   'grid;',
   '' };
  slide(5).text={
   ' Finally, here is the frequency content of the signal before and',
   ' after filtering.  Notice the peaks at 5 and 30 Hz have been',
   ' effectively eliminated.',
   ' >> S=fft(s,512);',
   ' >> SF=fft(sf,512);',
   ' >> w=(0:255)/256*(Fs/2);',
   ' >> plot(w,abs([S(1:256)'' SF(1:256)'']));',
   ' >> xlabel(''Frequency (Hz)'');',
   ' >> ylabel(''Mag. of Fourier transform'');'};
end