% [w,y,e,p]= asptdrnlms(x,w,d,mu,p,b,k)%%    Performs filtering and coefficient update using the %    Data Reusing Normalized Least Mean Squares (DRNLMS) %    algorithm. DRLMS updates the filter coefficients k %    times each iteration using the same set of data to %    speed the convergence process.% 	% Input Parameters [Size]:: %    x   : input samples delay line [L x 1]%    w   : filter coefficients vector w(n-1) [L x 1]%    d   : desired output d(n) [1 x 1]%    mu  : adaptation constant%    p   : last estimated power of x p(n-1) %    b   : AR pole for recursive calculation of p%    k   : number of data reusing cycles% Output parameters::%    w   : updated filter coefficients w(n)%    y   : filter output y(n)%    e   : error signal; e(n) = d(n)-y(n)%    p   : new estimated power of x p(n)%% SEE ALSO INIT_DRNLMS, ASPTNLMS, ASPTDRLMS, ASPTRDRNLMS.
%       Author : John Garas PhD.%       Version 2.1, Release October 2002.%       Copyright (c) DSP ALGORITHMS 2000-2002.