29 init_ lms

Purpose

Creates and initializes the variables required for the Least Mean Squares (LMS) Adaptive algorithm

Syntax

[w,x,d,y,e]=init_lms(L)
[w,x,d,y,e]=init_lms(L,w0,x0,d0)

Description

The variables of the LMS are summarized below (see Fig. 2.6).

Input Parameters [Size] :: 
   L   : number of filter coefficients
   w0  : initial coefficient vector [L x 1] 
   x0  : initial input samples vector [L x 1] 
   d0  : initial desired sample [a x 1] 
Output parameters [default] ::
   w   : initialized filter coefficients [zeros]
   x   : initialized input vector [zeros]
   d   : initialized desired sample [white noise]
   y   : Initialized filter output 
   e   : initialized error sample [e = d - y]

Example

L  = 5;           % Number of coefficients 
w0 = [0;0;1;0;0]; % initial filter coefficients 
x0 = rand(5,1);   % initial delay line
d0 = 0;           % desired sample

% Create and initialize an LMS FIR filter
[w,x,d,y,e]=init_lms(L,w0,x0,d0);

Remarks

• Supports both real and complex signals and filters.
• Use input parameters 2 through 4 to initialize the algorithm storage. This is helpful when the adaptation process is required to start from a known operation point calculated off-line or from previous simulations.

See Also

ASPTLMS, MODEL_ LMS.