solns8_600(2)

solns8_600(2) - ECE-600 Introduction to Digital Signal...

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Unformatted text preview: ECE-600 Introduction to Digital Signal Processing Autumn 2010 Homework #8 Dec. 4, 2010 HOMEWORK SOLUTIONS #8 1. The following code designed and plotted all filters. Plots were generated by my routine “ filter_plot ” that contains code very similar to that presented in the notes. F = [0,0.2,0.3,0.5,0.6,1]; % matlab-normalized frequencies A = [0,0,1,1,0,0]; % desired amplitudes D = [50,0.5,50]; % deviations (in positive dB) M = 1024; % # DFT points to use for DTFT % calculate linear ripple from dB deviations R = zeros(size(D)); for i=1:length(D), if A(2*i)==0, R(i) = 10^(-D(i)/20); % worst stopband ripple else, R(i) = 1-10^(D(i)/20); % worst passband ripple end; end; % calculate smallest transition band width Delta_f = min([-1,1]*reshape(F(2:end-1),2,length(F)/2-1)); Fc = 0.5*[1,1]*reshape(F(2:end-1),2,length(F)/2-1); % design hamming filter L=ceil(3.3/((Delta_f*pi)/(2*pi)))-13; h=fir1(L-1,[1.06*Fc(1),0.975*Fc(2)],hamming(L)); h=h*(1-0.9*R(2)); figure(1) filter_plot(h,1,M,F,A,D); title([’hamming, L=’,num2str(L)]); % design kaiser filter [N,Fk,beta,filt_type] = kaiserord(F(2:end-1),A(1:2:end),abs(R)); L=N-10; h=fir1(L-1,[1.051*Fk(1),0.975*Fk(2)],kaiser(L,1.05*beta)); h=h*(1-0.95*R(2)); figure(2) filter_plot(h,1,M,F,A,D); title([’kaiser, L=’,num2str(L)]); % design WLS filter L=44; h=firls(L-1,[0,0.205,0.310,0.49,0.595,1],A,[1.3/R(1),0.5/R(2),1.1/R(3)]); h=h*(1-0.75*R(2)); figure(3) filter_plot(h,1,M,F,A,D); title([’weighted LS, L=’,num2str(L)]); % design equiripple filter [N,F,A,W]=firpmord(F(2:end-1),A(1:2:end),abs(R)); L=N+7; h=firpm(L-1,F,A,W); figure(4) filter_plot(h,1,M,F,A,D); title([’equiripple, L=’,num2str(L)]); % design butterworth filter [N,fc] = buttord(F(3:4),[F(2),F(5)],2*D(2),D(1)+D(2)); [b,a] = butter(N,fc);...
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This note was uploaded on 03/05/2011 for the course ECE 600 taught by Professor Clymer,b during the Fall '08 term at Ohio State.

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solns8_600(2) - ECE-600 Introduction to Digital Signal...

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