Constrained L2 bandpass FIR filter design
Constrained least square band-pass FIR filter design without specified transition bands.
cl2bp(m = 30, w1, w2, up, lo, L = 2048)
m |
degree of cosine polynomial, resulting in a filter of length
|
w1, w2 |
bandpass filter cutoffs in the range |
up |
vector of 3 upper bounds for c(stopband1, passband, stopband2). |
lo |
vector of 3 lower bounds for c(stopband1, passband, stopband2). |
L |
search grid size; larger values may improve accuracy, but greatly increase calculation time. Default: 2048, maximum: 1e6. |
This is a fast implementation of the algorithm cited below. 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
The FIR filter coefficients, a vector of length 2 * m + 1, of
class Ma.
Ivan Selesnick, Rice University, 1995,
downloaded from https://www.ece.rice.edu/dsp/software/cl2.shtml.
Conversion to R by Geert van Boxtel, G.J.M.vanBoxtel@gmail.com.
Selesnick, I.W., Lang, M., and Burrus, C.S. (1998) A modified
algorithm for constrained least square design of multiband FIR filters
without specified transition bands. IEEE Trans. on Signal Processing,
46(2), 497-501.
https://www.ece.rice.edu/dsp/software/cl2.shtml
w1 <- 0.3 * pi w2 <- 0.6 * pi up <- c(0.02, 1.02, 0.02) lo <- c(-0.02, 0.98, -0.02) h <- cl2bp(30, w1, w2, up, lo, 2^11) freqz(h)
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