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To create a FIR filter which matches a desired inverse filter, use the built in MATLAB filter design program called fir2 [b = fir2(n,f,m)]. This designs an n order FIR filter which attempts to create an FIR filter whose spectrum matches a linear interpolation between input amplitudes m at frequencies f. The coefficients (b) are obtained by applying an inverse Fourier transform to m at frequencies f and multiplying by a window. In creating an inverse filter, the default Hamming window is acceptable because it provides a balance between the dynamic range and the resolution of the signal. The response of the inverse filter at different frequencies should not be so different that a huge dynamic range is required. Finally enter these coefficients into the TI chip and produce an FIR filter.
h=fir2(62, ((10.^(linspace(0,1,length(targetfft))'))-1)/9,targetfft);
The FIR2 command with 64 coefficients does an acceptable job of matching the shape of an ideal inverse filter. However, given more memory and more coefficients one could do any even better job of matching the ideal.
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