[SciPy-Dev] SciPy Goal
Thu Jan 5 10:14:45 CST 2012
On Jan 5, 2012, at 10:00 AM, email@example.com wrote:
> On Thu, Jan 5, 2012 at 10:32 AM, Neal Becker <firstname.lastname@example.org> 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
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"
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