9 init_ sovtdlms

Purpose

Creates and initializes the variables required for the Second Order Volterra Transform Domain LMS Adaptive filter.

Syntax

[W,w,x,d,y,e,p] = init_sovtdlms(L1,L2)
[W,w,x,d,y,e,p] = init_sovtdlms(L1,L2,W0,x0,d0)

Description

The second order Volterra TDLMS filter consists of a linear filter part of length L1 and a nonlinear filter part. The nonlinear part uses the combination of cross-products between samples in the delay line. The number of past samples used in the nonlinear part is defined by the L2 parameter. A value of L2=0 reduces the Volterra filter to a linear TDLMS filter. The variables of the SOVTDLMS are summarized below.

Input Parameters [Size]:: 
  L1  : memory length of the linear part of the  filter
  L2  : memory length of the nonlinear part of the  filter
  w0  : initial T-domain coef. vector [L1 + sum(1:L2) x 1] 
  x0  : initial input samples vector [L1 + sum(1:L2) x 1] 
  d0  : initial desired sample [1 x 1] 
Output parameters [default]::
  W   : initialized T-domain coef. vector [zeros]
  w   : initialized time-domain coef. vector [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

L1 = 3;           % Memory of linear filter
L2 = 2;           % Memory of nonlinear filter 
W0 = zeros(6,1);  % initial filter coefficients 
x0 = rand(6,1);   % initial delay line
d0 = 0;           % desired sample

% Create and initialize a SOVTDLMS FIR filter
[W,w,x,d,y,e,p]=init_sovtdlms(L1,L2,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

ASPTSOVTDLMS.