Least squares FIR digital filter design with prescribed magnitude AND phase response using Levinson's algorithm

levin.m

function x = levin(a,b)
% function x = levin(a,b)
% solves system of complex linear equations toeplitz(a)*x=b
% using Levinson's algorithm
% a ... first row of positive definite Hermitian Toeplitz matrix
% b ... right hand side vector
%
% Author: Mathias C. Lang, Vienna University of Technology, AUSTRIA
% 1997-09
% [email protected]

a = a(:); b = b(:); n = length(a);
t = 1; alpha = a(1); x = b(1)/a(1);
for i = 1:n-1,
   k = -(a(i+1:-1:2)'*t)/alpha;
   t = [t;0] + k*flipud([conj(t);0]);
   alpha = alpha*(1 - abs(k)^2);
   k = (b(i+1) - a(i+1:-1:2)'*x)/alpha;
   x = [x;0] + k*flipud(conj(t));
end

lslevin.m

function h = lslevin(N,om,D,W)
% h = lslevin(N,om,D,W)
% Complex Least Squares FIR filter design using Levinson's algorithm
%
% h      filter impulse response
% N      filter length
% om     frequency grid (0 <= om <= pi)
% D      complex desired frequency response on the grid om
% W      positive weighting function on the grid om
%
% example: length 61 bandpass, band edges [.23,.3,.5,.57]*pi,
% weighting 1 in passband and 10 in stopbands, desired passband
% group delay 20 samples
%
% om=pi*[linspace(0,.23,230),linspace(.3,.5,200),linspace(.57,1,430)];
% D=[zeros(1,230),exp(-j*om(231:430)*20),zeros(1,430)];
% W=[10*ones(1,230),ones(1,200),10*ones(1,430)];
% h = lslevin(61,om,D,W);
%
% Author: Mathias C. Lang, Vienna University of Technology
% 1998-07
% [email protected]

om = om(:); D = D(:); W = W(:); L = length(om);
DR = real(D); DI = imag(D); a = zeros(N,1); b = a;

% Set up vectors for quadratic objective function
% (avoid building matrices)
dvec = D; evec = ones(L,1); e1 = exp(j*om);
for i=1:N,
   a(i) = W.'*real(evec);
   b(i) = W.'*real(dvec);
   evec = evec.*e1; dvec = dvec.*e1;
end

a=a/L; b=b/L;

% Compute weighted l2 solution
h = levin(a,b);