We have sets of ADC data collected with different front-end filters at acquisition; given an empirically determined roll off in dB/octave or dB/Hz, I'd like to perform equalization (in this case the low frequencies) and I know from sweeps that roll off begins under ~200Hz and -3dB is ~15Hz. One general example is Bank's algorithm: <http://nullege.com/codes/show/src@p@o@porc-HEAD@porc.py>http://nullege.com/codes/show/src@p@o@porc-HEAD@porc.py where people correct sound for their room acoustics. There is also the Nelson-Kirkeby inverse filter methodology. Our specific case is flattening the response due to a single-pole RC high-pass filter so I think remez() might be just fine; can anyone here supply links or examples in scipy to this application of remez()? I'm guessing scipy.signal.remez( 2, range(.625, 512, .625), desired= <inverse of measured gain, range(.625, 256, .625)>, weight=<unsure of this...>, Hz=1024, type=<unsure, what to use for high-pass?>, maxiter=25, grid_density=16 ) - Ray