sem2 done
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207
semestralka2/spd_sumu.m
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207
semestralka2/spd_sumu.m
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clc;
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close all;
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clear;
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% === Global figure styling (light mode defaults) ===
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set(0, 'DefaultFigureColor', 'w'); % white figure background
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set(0, 'DefaultAxesColor', 'w'); % white plotting area
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set(0, 'DefaultAxesXColor', 'k'); % black x-axis lines and text
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set(0, 'DefaultAxesYColor', 'k'); % black y-axis lines and text
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set(0, 'DefaultTextColor', 'k'); % black text for titles, labels
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set(0, 'DefaultLineColor', 'b'); % blue lines by default
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clear saveFigure
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% === Automatic figure export counter ===
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fig_counter = 1;
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save_fig = @saveFigure;
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function saveFigure(name)
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persistent counter
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if isempty(counter)
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counter = 1;
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end
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% Force painters renderer and white backgrounds
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set(gcf, 'Renderer', 'painters');
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set(gcf, 'Color', [1 1 1]);
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axesHandles = findall(gcf, 'Type', 'axes');
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for ax = axesHandles'
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set(ax, 'Color', [1 1 1]);
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end
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% Export clean EPS with no transparency problems
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print(gcf, '-depsc2', '-r300', '-painters', sprintf('%d_%s.eps', counter, name));
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counter = counter + 1;
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end
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[y1, Fs1] = audioread('flac.wav');
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[y2, Fs2] = audioread('flac2.wav');
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% Časové priebehy
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t1 = (0:length(y1)-1)/Fs1;
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t2 = (0:length(y2)-1)/Fs2;
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figure;
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subplot(2,1,1);
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plot(t1, y1);
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xlabel('Čas [s]');
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ylabel('Amplitúda');
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title('flac.wav');
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grid on;
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subplot(2,1,2);
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plot(t2, y2, 'r');
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xlabel('Čas [s]');
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ylabel('Amplitúda');
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title('flac2.wav');
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grid on;
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save_fig('time'); fig_counter = fig_counter + 1;
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% Fourierova transformácia
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N1 = length(y1);
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N2 = length(y2);
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X1 = fft(y1);
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X2 = fft(y2);
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freq_shift1 = (-N1/2 : N1/2 - 1) * (Fs1 / N1);
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freq_shift2 = (-N2/2 : N2/2 - 1) * (Fs2 / N2);
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% Real a imag časť spektra
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figure;
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subplot(2,1,1);
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plot(freq_shift2, real(fftshift(X2)));
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xlabel('Frekvencia [Hz]');
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ylabel('Amplitúda');
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title('flac2.wav – Reálna časť spektra');
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xlim([-550 550]);
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grid on;
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subplot(2,1,2);
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plot(freq_shift2, imag(fftshift(X2)), 'r');
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xlabel('Frekvencia [Hz]');
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ylabel('Amplitúda');
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title('flac2.wav – Imaginárna časť spektra');
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xlim([-550 550]);
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grid on;
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save_fig('spectrum'); fig_counter = fig_counter + 1;
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% Real a imag časť spektra
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figure;
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subplot(2,1,1);
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plot(freq_shift1, real(fftshift(X1)));
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xlabel('Frekvencia [Hz]');
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ylabel('Amplitúda');
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title('flac.wav – Reálna časť spektra');
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xlim([-3500 3500]);
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grid on;
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subplot(2,1,2);
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plot(freq_shift1, imag(fftshift(X1)), 'r');
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xlabel('Frekvencia [Hz]');
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ylabel('Amplitúda');
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title('flac.wav – Imaginárna časť spektra');
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xlim([-3500 3500]);
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grid on;
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save_fig('spectrum2'); fig_counter = fig_counter + 1;
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% Určenie typu šumu na základe spektrálneho sklonu
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[PSD, f] = pwelch(y1, hamming(4096), [], [], Fs1, 'onesided'); % PSD
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mask = f > 10 & f < Fs1/2;
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logf = log10(f(mask));
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logP = log10(PSD(mask));
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p = polyfit(logf, logP, 1);
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slope = p(1);
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intercept = p(2);
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fprintf('Spektrálny sklon (alfa) = %.2f\n', slope);
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% Vizualizácia
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figure;
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loglog(f, PSD); hold on;
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loglog(f(mask), 10.^(polyval(p, logf)), 'r', 'LineWidth', 1.5);
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xlabel('Frekvencia [Hz]');
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ylabel('Výkonová spektrálna hustota (PSD)');
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title(sprintf('Spektrálny sklon = %.2f', slope));
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lgd = legend('Meraná PSD', 'Lineárna aproximácia (log-log)', 'Location', 'best');
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set(lgd, 'Color', 'w', 'TextColor', 'k');
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grid on;
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save_fig('spectral_slope'); fig_counter = fig_counter + 1;
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% === IIR Notch filtering flac2.wav and noise type analysis ===
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fprintf('\n=== IIR Notch Filtering of flac2.wav ===\n');
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% Detekcia dominantných frekvencií v flac2.wav pre notch filtráciu
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halfN = floor(N2 / 2);
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freq_pos = (0:halfN - 1) * (Fs2 / N2);
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magX2 = abs(X2(1:halfN));
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[pks2, locs2] = findpeaks(magX2, 'NPeaks', 3, 'SortStr', 'descend');
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f_notch = sort(freq_pos(locs2));
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fprintf('\nDetekované dominantné frekvencie vo flac2.wav:\n');
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fprintf(' %.1f Hz\n', f_notch);
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% === Konštrukcia a aplikácia IIR notch filtra ===
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r = 0.98; % ostrosť zárezu (0.98 až 0.995)
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Fs = Fs2;
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sos_notch = zeros(length(f_notch), 6);
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for k = 1:length(f_notch)
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theta = 2 * pi * (f_notch(k) / Fs);
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b = [1, -2*cos(theta), 1];
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a = [1, -2*r*cos(theta), r^2];
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sos_notch(k, :) = [b, a];
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end
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% Aplikácia filtra na flac2.wav
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y2_notched = sosfilt(sos_notch, double(y2));
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% Uloženie výsledného signálu
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audiowrite('flac2_notched.wav', y2_notched / max(abs(y2_notched)), Fs2);
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% Zobrazenie pred/po filtrácii
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figure;
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subplot(2,1,1);
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plot(y2);
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xlabel('Vzorky'); ylabel('Amplitúda');
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title('Pôvodný signál flac2.wav');
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grid on;
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subplot(2,1,2);
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plot(y2_notched, 'r');
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xlabel('Vzorky'); ylabel('Amplitúda');
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title('Filtrovaný signál – flac2.wav (IIR Notch)');
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grid on;
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save_fig('flac2_notched'); fig_counter = fig_counter + 1;
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% === Analýza zvyškového šumu po IIR filtri ===
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[PSD_res, f_res] = pwelch(y2_notched, hamming(4096), [], [], Fs2, 'onesided');
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mask_res = f_res > 10 & f_res < Fs2/2;
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logf_res = log10(f_res(mask_res));
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logP_res = log10(PSD_res(mask_res));
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p_res = polyfit(logf_res, logP_res, 1);
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slope_res = p_res(1);
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fprintf('\nSpektrálny sklon po IIR filtrácii (alfa) = %.2f\n', slope_res);
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% Vizualizácia
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figure;
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loglog(f_res, PSD_res); hold on;
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loglog(f_res(mask_res), 10.^(polyval(p_res, logf_res)), 'r', 'LineWidth', 1.5);
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xlabel('Frekvencia [Hz]');
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ylabel('Výkonová spektrálna hustota (PSD)');
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title(sprintf('Zvyškový šum po IIR notch filtrácii (α = %.2f)', slope_res));
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legend('PSD po IIR filtri', 'Lineárna aproximácia', 'Location', 'best');
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grid on;
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save_fig('residual_noise_flac2'); fig_counter = fig_counter + 1;
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% Interpretácia typu šumu podľa alfa
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if slope_res > -0.5
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noise_type = 'biely šum';
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elseif slope_res > -1.5
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noise_type = 'ružový šum';
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else
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noise_type = 'hnedý šum';
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end
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fprintf('Typ zostávajúceho šumu po notch filtrácii: %s\n', noise_type);
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