Problem with standard methods of smoothening in Signals
Explore common problems with signal smoothening methods in MATLAB. Learn effective techniques to overcome challenges and enhance your signal processing. Read mo
Explore common problems with signal smoothening methods in MATLAB. Learn effective techniques to overcome challenges and enhance your signal processing. Read mo
% Generate noisy signal (example) fs = 1000; % Sampling frequency t = 0:1/fs:5; % Time vector signal = sin(2*pi*10*t) + 0.5*sin(2*pi*50*t) + 2*randn(size(t)); % Noisy signal % Design high-pass filter to remove low-frequency drift highpass_cutoff = 0.5; % Cutoff frequency for high-pass filter (adjust as needed) hp_filter = designfilt('highpassfir', 'FilterOrder', 50, 'CutoffFrequency', highpass_cutoff, 'SampleRate', fs); % Design low-pass filter to attenuate high-frequency noise lowpass_cutoff = 30; % Cutoff frequency for low-pass filter (adjust as needed) lp_filter = designfilt('lowpassfir', 'FilterOrder', 50, 'CutoffFrequency', lowpass_cutoff, 'SampleRate', fs); % Apply high-pass filter filtered_signal = filtfilt(hp_filter, signal); % Apply low-pass filter filtered_signal = filtfilt(lp_filter, filtered_signal); % Plot original and filtered signals figure; plot(t, signal, 'b', 'LineWidth', 1.5); hold on; plot(t, filtered_signal, 'r', 'LineWidth', 1.5); xlabel('Time (s)'); ylabel('Amplitude'); legend('Original Signal', 'Filtered Signal'); title('Cascaded High-pass and Low-pass Filtering'); grid on;
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