30 init_ mvsslms

Purpose

Creates and initializes the variables required for the Modified Variable Step Size Least Mean Squares (MVSSLMS) Adaptive algorithm

Syntax

[w,x,d,y,e,g,mu] = init_mvsslms(L)
[w,x,d,y,e,g,mu] = init_mvsslms(L,w0,x0,d0,mu0,g0)

Description

The MVSSLMS is a simplified version of the VSSLMS. The variables of the MVSSLMS are summarized below (see Fig. 2.6).

Input Parameters [Size] :: 
  L    : adaptive filter length
  w0   : initial vector of filter coefficients [Lx1]
  x0   : initial input samples delay line [Lx1]
  d0   : initial desired sample [1x1]
  mu0  : initial step-size [1x1]
  g0   : initial gradient[1x1]

Output parameters [default]::
   w   : initialized filter coefficients [zeros]
   x   : initialized input delay line [zeros]
   d   : initialized desired sample [white noise]
   y   : Initialized filter output
   e   : initialized error sample [e = d - y]
   g   : initialized gradient vector [zero]
   mu  : initialized step-size vector [zero]

Example

L   = 5;             % Number of coefficients 
w0  = [0;0;1;0;0];   % initial filter coefficients 
x0  = rand(5,1);     % initial delay line
mu0 = 0.1;           % initial step sizes

% Create and initialize an MVSSLMS FIR filter
[w,x,d,y,e,g,mu] = init_mvsslms(L,w0,x0,[],mu0);

Remarks

• Supports both real and complex signals and filters.
• Use input parameters 2 through 6 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

ASPTMVSSLMS, ASPTVSSLMS, MODEL_ MVSSLMS.