Finine impulse response (FIR) filter using least-squares error minimization.



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%pylab inline









    



Populating the interactive namespace from numpy and matplotlib



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from scipy import signal



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signal.firls?



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# filter parameters
srate   = 1024 # samples per second
nyquist = srate/2
frange  = [20,45] # range of frequencies (lower than Nyquist)
transw  = .1 # transition zone is 10%
order   = int( 5*srate/frange[0] )



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256



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