asptlms.m

卡尔曼滤波器设计的一个例子

% [w,y,e]= asptlms(x,w,d,mu,alg)	
%
%    Performs filtering and coefficient update using the 
%    Least Mean Squares Adaptive algorithm.
% 	
% Input Parameters [size] :: 
%    x   : vector of input samples [L x 1]
%    w   : vector of filter coefficients w(n-1) [L x 1]
%    d   : desired output d(n) [1 x 1]
%    mu  : adaptation constant
%    alg : specifies the variety of the lms to use in the 
%          update equation. Must be one of the following: 
%          'lms'     [default] 
%          'slms'  - sign LMS, uses sign(e)
%          'srlms' - signed regressor LMS, uses sign(x)
%          'sslms' - sign-sign LMS, uses sign(e) and sign(x)
% Output parameters ::
%    w   : updated filter coefficients w(n)
%    y   : filter output y(n)
%    e   : error signal; e(n) = d(n) - y(n)
%
% SEE ALSO INIT_LMS, MODEL_LMS, ASPTNLMS, ASPTVSSLMS, ASPTLCLMS.

%       Author : John Garas PhD.
%       Version 2.1, Release October 2002.
%       Copyright (c) DSP ALGORITHMS 2000-2002.