cl2bp function

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)

Arguments

• m: degree of cosine polynomial, resulting in a filter of length 2 * m + 1. Must be an even number. Default: 30.
• w1, w2: bandpass filter cutoffs in the range 0 <= w1 < w2 <= pi, where pi is the Nyquist frequency.
• 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.

Returns

The FIR filter coefficients, a vector of length 2 * m + 1, of class Ma.

Details

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

Examples

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)

References

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

See Also

Ma, filter, remez

Author(s)

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 .