CODEWITHSUNDEEP
pythonscipysignal-processingfftspectral-density
John Choi
John Choi

Reputation: 31

Usage of signal.welch

I want to use python signal.welch. The usage of signal.welch is as follows,

f, Pxx_den = signal.welch(x, fs, nperseg=1024)

In my case, x is for example gyroscopy signal ( 1 x 1024 samples (for about 10 sec data)), fs = 100 Hz. In my case, how can I decide nperseg? I want to know how I can select nperseg when the number of samples of the input is 1024 (about 10 sec).

Upvotes: 3

Views: 9247

Answers (1)

Pascal Getreuer
Pascal Getreuer

Reputation: 3271

scipy.signal.welch estimates the power spectral density by dividing the data into segments and averaging periodograms computed on each segment. The nperseg arg is the segment length and (by default) also determines the FFT size.

On the one hand, making nperseg smaller allows the input to divide into more segments, good for more averaging to get a more reliable estimate. On the other hand, making nperseg larger improves the frequency resolution of the result. In any case, nperseg should be smaller than the input size in order to get multiple segments.

The default segment length is 256 samples, which seems like a reasonable starting point for a 1024-sample input.

Upvotes: 5

Related Questions