Low pass filter using FFT instead of convolution implementation

Question

Implementing a low pass FIR filter, when should one use FFT and IFFT instead of time-domain convolution?

The goal is to achieve the lowest CPU time required for rea

Answer 1

Convolution is actually O(m*n) where m is the width of the finite impulse response, and N the sample window.

So the tipping point of m where it is useful to change to FFT+IFFT is related to log(N) of the sample window.

In realtime operation the fact that FFT is batch oriented might be more important than the relative amount of clock cycles, as it may not be acceptable to wait 1024 sample points before filtering, if the application is in a regulation loop for example.

Now a lot of development has been done is this area and plenty of code is available, so trying a couple of solutions and benchmarking is key here.