In an attempt to computationally invert the effect of an analog RC filter on a data set and reconstruct the "true" signal, a co-worker suggested: "Mathematically, you just reverse the a and b parameters. Then the zeros become the poles, but if the new poles are not inside the unit circle, the filter is not stable." So, to "stabilize" the poles' issue seen, I test for the DIV/0 error and set it to 2./N+0.j in scipy/signal/filter_design.py ~ line 244 d = polyval(a[::-1], zm1) if d[0]==0.0+0.j: d[0] = 2./N+0.j h = polyval(b[::-1], zm1) / d - Question is, is this a mathematically valid treatment? - Is there a better way to invert a Butterworth filter, or work with the DIV/0 that occurs without modifying the signal library? - Should I post to *-users instead? I noted d[0] > 2./N+0.j makes the zero bin result spike low; 2/N gives a reasonable "extension" of the response curve. This whole tweak causes a zero offset however, which I remove. An example attached... Ray Schumacher Programmer/Consultant