Harmonic distortion of a input signal

[Christian Gollwitzer]

Oops, I thought we were posting to comp.dsp. Nevertheless, I think 
numpy.fft does mixed-radix (can't check it now)

Am 20.05.13 19:50, schrieb Christian Gollwitzer:
> Am 20.05.13 19:23, schrieb jmfauth:
>> Non sense.
>
> Dito.
>
>> The discrete fft algorithm is valid only if the number of data
>> points you transform does correspond to a power of 2 (2**n).
>
> Where did you get this? The DFT is defined for any integer point number
> the same way.
>
> Just if you want to get it fast, you need to worry about the length. For
> powers of two, there is the classic Cooley-Tukey. But there do exist FFT
> algorithms for any other length. For example, there is the Winograd
> transform for a set of small numbers, there is "mixed-radix" to reduce
> any length which can be factored, and there is finally Bluestein which
> works for any size, even for a prime. All of the aforementioned
> algorithms are O(log n) and are implemented in typical FFT packages. All
> of them should result (up to rounding differences) in the same thing as
> the naive DFT sum. Therefore, today
>
>> Keywords to the problem: apodization, zero filling, convolution
>> product, ...
>
> Not for a periodic signal of integer length.
>
>> eg. http://en.wikipedia.org/wiki/Convolution
>
> How long do you read this group?
>
>      Christian
>