35 init_ rdrnlms

Purpose

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

Syntax

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

Description

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

Input Parameters [Size]:: 
  L  : number of filter coefficients
  k  : number of data reusing cycles.
  w0 : initial coefficient vector [L x 1] 
  x0 : initial input samples vector [L+k x 1] 
  d0 : initial desired sample [k+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 vector [d - y]
  p  : initialized power estimate

Example

L  = 5;             % Number of coefficients 
k  = 2;             % number of reusing cycles
w0 = [0;0;1;0;0];   % initial filter coefficients 
x0 = rand(L+k,1);   % initial delay line
d0 = rand(k+1,1);   % desired sample

% Create and initialize a RDRNLMS FIR filter
[w,x,d,y,e,p]=init_rdrnlms(L,k,w0,x0,d0);

Remarks

• Supports both real and complex signals and filters.
• Use input parameters 3 through 5 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

ASPTRDRNLMS.