Hi John
The signals should be zero-padded, otherwise you get circular convolution:
F = npy.fft.fft(r,len(r)+len(x)-1)
X = npy.fft.fft(x,len(r)+len(x)-1)
Y = F*X
yi = npy.fft.ifft(Y)[:len(x)].real
Also take a look at fftconv.
Regards
Stéfan
On Thu, Oct 25, 2007 at 01:00:29PM -0500, John Hunter
I am working on an example to illustrate convolution in the temporal
and spectral domains, using the property that a convolution in the
time domain is a multiplication in the fourier domain. I am using
numpy.fft and numpy.convolve to compute the solution two ways, and
comparing them. I am getting
