Examples
h = cl2bp(5, 0.3*pi, 0.6*pi, [0.02, 1.02, 0.02], [-0.02, 0.98, -0.02], 2^11) h = 0.038311 0.082289 -0.086163 -0.226006 0.047851 0.307434 0.047851 -0.226006 -0.086163 0.082289 0.038311 |  |  |
Constrained L2 bandpass FIR filter design.
h = cl2bp (m, w1, w2, up, lo, gridsize) h = cl2bp (m, w1, w2, up, lo)
degree of cosine polynomial, i.e. the number of output coefficients will be m*2+1
bandpass filter cutoffs in the range 0 <= w1 < w2 <= pi, where pi is the Nyquist frequency
vector of 3 upper bounds for [stopband1, passband, stopband2]
vector of 3 lower bounds for [stopband1, passband, stopband2]
search grid size; larger values may improve accuracy, but greatly increase calculation time.
This is an Octave function. Constrained L2 bandpass FIR filter design. Compared to remez, it offers implicit specification of transition bands, a higher likelihood of convergence, and an error criterion combining features of both L2 and Chebyshev approaches.
h = cl2bp(5, 0.3*pi, 0.6*pi, [0.02, 1.02, 0.02], [-0.02, 0.98, -0.02], 2^11) h = 0.038311 0.082289 -0.086163 -0.226006 0.047851 0.307434 0.047851 -0.226006 -0.086163 0.082289 0.038311 | | |