[SciPy-Dev] SciPy Goal

Travis Oliphant travis@continuum...
Thu Jan 5 10:14:45 CST 2012

On Jan 5, 2012, at 10:00 AM, josef.pktd@gmail.com wrote:

> On Thu, Jan 5, 2012 at 10:32 AM, Neal Becker <ndbecker2@gmail.com> wrote:
>> Some comments on signal processing:
>> Correct me if I'm wrong, but I think scipy signal (like matlab) implement only a
>> general purpose filter, which is an IIR filter, single rate.  Efficiency is very
>> important in my work, so I implement many optimized variations.
>> Most of the time, FIR filters are used.  These then come in variations for
>> single rate, interpolation, and decimation (there is also another design for
>> rational rate conversion).  Then these have variants for scalar/complex
>> input/output, as well as complex in/out with scalar coefficients.
>> IIR filters are seperate.
>> FFT based FIR filters are another type, and include both complex in/out as well
>> as scalar in/out (taking advantage of the 'two channel' trick for fft).
> just out of curiosity: why no FFT base IIR filter?
> It looks like a small change in the implementation, but it is slower
> than lfilter for shorter time series so I mostly dropped fft based
> filtering.

I think he is talking about filter design, correct?  

lfilter can be used to implement FIR and IIR filters -- although an FIR filter is easily computed with convolve/correlate as well. 

FIR filter design is usually done in the FFT-domain.   But, this picks the coefficients for the actual filtering itself done with something like convolve

If you *do* filtering in the FFT-domain than it's usually going to be IIR.   What are you referring to when you say "small change in the implementation"


> Josef
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