26 init_ drnlms

Purpose

Creates and initializes the variables required for the Data Reusing Normalized Least Mean Squares algorithm.

Syntax

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

Description

The variables of the DRNLMS 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 [1 x 1] 

Output parameters [default]::
  w  : initialized filter coefficients [zeros]
  x  : initialized input vector [white noise]
  d  : initialized desired sample [white noise]
  y  : Initialized filter output
  e  : initialized error sample [e = d - y]
  p  : initialized power estimate

Example

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

% Create and initialize a DRNLMS FIR filter
[w,x,d,y,e,p]=init_drnlms(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

ASPTDRNLMS.