Python中3D音频信号的平均RMS值

Question

I am quite new to programming and Python. I am working on a project in which I built an Auditory filterbank with two banks of Gammatone filters. Now I ended up with a 39x10x8545 matrix. I want to calculate the average of rms energy across the time axis (over the 8545) to reduce the dimensionality of the signal. Can anyone suggest me a better method to do it efficiently in Python because I cannot afford much memory due to the audio signal being very large. Thanks in advance.

Answer 1

The RMS of is signal is the root mean squared, which is not the same as the mean. So you need to perform the RMS calculation.

math.sqrt(numpy.mean(x*x))

There are several other pages on this site that discuss this in further: here , here , here

Answer 2

I would like to answer this question myself based on Djmoffat's answer. I tried his answer but found that the numpy.pow() gave me very slow results. So I tried using

math.sqrt(numpy.mean(x**2)) 

This gave me faster results. I understand that math.pow() is slow as it has to consider many other things like fractional powers and other things clearly discussed here . The context is important as I am sure I will have just the integer powers and more precisely '2'.