62 lines
2.0 KiB
Matlab
62 lines
2.0 KiB
Matlab
%% Funkcionalo un logisko shemu modelesana
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% Laboratorijas darbs Nr.3.
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% sinusoidu generesana un filtresana
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% Autors: Imants Pulkstenis
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%
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% Apliecibas Nr.021REB152
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%% 1.Sakuma dati
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%
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% Piemers:https://la.mathworks.com/help/simulink/slref/digital-waveform-generation-approximating-a-sine-wave.html
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%
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clear; format shortEng;
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fs = 22050; % (ciparu dalas sample clock) = 22050 (audio standarts).
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k = 52; % k - studenta apliecibas pedejie 2 cipari
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f1 = 32 * k;
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f2 = 48 * k;
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%% 2.FIR bandpass filtrs
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n1 = 40; % First filter order
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n2 = 40; % Second filter order
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band = 100; % filter bandwidth
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fsh = fs/2; % corresponding to half the sample rate
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Wn1= f1/fsh; % The cut-off frequency Wn must be between 0 < Wn < 1.0, with 1.0 corresponding to half the sample rate.
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Wn2= f2/fsh;
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b1 = fir1(n1,[Wn1-band/(fsh*2) Wn1+band/(fsh*2) ], 'bandpass'); % Window-based FIR filter design
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b2 = fir1(n2,[Wn2-band/(fsh*2) Wn2+band/(fsh*2) ], 'bandpass'); % Window-based FIR filter design
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[h1,w1] = freqz(b1);
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[h2,w2] = freqz(b2);
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figure (1)
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plot (w1/pi,db(h1), ...
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w2/pi,db(h2),...
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[Wn1 Wn1],[3 -80], '--', ...
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[Wn2 Wn2], [3 -80], '--',...
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[0 1],[-20 -20], '--')
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axis([0 1 -80 3])
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grid on,
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xlabel('Normalized Frequency (\times\pi rad/sample)')
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ylabel('Magnitude (dB)')
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legend('Response FIR_1','Response FIR_2','f_1','f_2', '-20dB target', 'Location','East')
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title('Magnitude response')
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%% 3.IIR bandpass filtrs
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[bb1,aa1] = iirpeak(Wn1,2*(Wn2-Wn1),-22); %Wo must satisfy 0.0 < Wo < 1.0, with 1.0 corresponding to pi radians/sample
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[h3,w3] = freqz(bb1,aa1);
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[bb2,aa2] = iirpeak(Wn2,2*(Wn2-Wn1),-19);
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[h4,w4] = freqz(bb2,aa2);
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figure (2)
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plot (w3/pi,db(h3), ...
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w4/pi,db(h4),...
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[Wn1 Wn1],[3 -80], '--', ...
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[Wn2 Wn2], [3 -80], '--',...
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[0 1],[-20 -20], '--')
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axis([0 1 -80 3])
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grid on,
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xlabel('Normalized Frequency (\times\pi rad/sample)')
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ylabel('Magnitude (dB)')
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legend('Response IIR_1','Response IIR_2','f_1','f_2', '-20dB target', 'Location','East')
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title('Magnitude response')
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