noise detector in matlab

To implement a basic noise detector in MATLAB, you can follow these steps:

1. Import your audio signal into MATLAB using the audioread function.

main.m
[y,fs] = audioread('filename.wav');
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2. Apply a bandpass filter to your signal to remove any unwanted frequencies. You can use the bandpass or designfilt functions for this step.

main.m
Wn = [1000 5000]/(fs/2);
[b,a] = butter(4,Wn,'bandpass');
filtered_signal = filtfilt(b,a,y);
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3. Compute the power spectral density of your signal using the pwelch function. This will give you an estimate of the power at each frequency in your signal.

main.m
nfft = 1024;
[Pxx,f] = pwelch(filtered_signal,hamming(nfft),nfft/2,nfft,fs);
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4. Calculate a noise threshold based on the power spectral density of your signal. This can be done by taking the median or mean of the power spectral density and multiplying it by a factor that depends on the characteristics of your particular noise.

main.m
threshold_factor = 10;
threshold = median(Pxx) * threshold_factor;
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5. Apply the threshold to the power spectral density of your signal to obtain a binary noise mask. You can use a simple thresholding function for this step.

main.m
noise_mask = Pxx > threshold;
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6. Apply the noise mask to your original signal to remove the identified noise. You can set the values in your original signal to zero where the noise mask is true.

main.m
noise_removed_signal = y;
noise_removed_signal(noise_mask) = 0;
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This is a basic implementation of a noise detector in MATLAB that uses filtering and thresholding. Depending on the characteristics of your particular noise, you may need to adjust the filter parameters and threshold factor to obtain optimal performance.