12 init_ lmslattice

Purpose

Creates and initializes the variables required for the LMS Lattice Joint Process Estimator.

Syntax

[k,c,b,P,d,y,e]=init_lmslattice(L)
[k,c,b,P,d,y,e]=init_lmslattice(L,k0,c0,b0,P0,d0)

Description

Figure 5.18: Block diagram of the LMS-LATTICE Joint Process Estimator.

The LMS-Lattice joint process estimator simultaneously adapts the PARCOR coefficients of a lattice predictor and the coefficients of the linear combiner as shown in Fig. 5.18. The variables of the LMS-LATTICE algorithms are summarized below.

Input Parameters [Size]:: 
   L   : number of linear combiner coefficients
   k0  : initial lattice predictor coefficients [Lx1]
   c0  : initial linear combiner coefficients [Lx1]
   b0  : initial backward prediction errors [Lx1]
   P0  : initial power of b [Lx1]
   d0  : initial desired sample [1x1]

Output parameters [default]::
   k   : lattice predictor coefficients [zeros]
   c   : linear combiner coefficients [zeros]
   b   : backward prediction errors [white noise]
   P   : estimated power of b [b .* b]
   d   : desired response [white noise]
   y   : linear combiner output [c' * b]
   e   : error signal [e = d - y]

Example

L  = 5;                 % Number of lattice stages 
k0 = zeros(L,1);        % initial PARCOR coefficients 
c0 = zeros(L,1);        % initial linear combiner coef.
b0 = rand(L,1);         % initial backward errors
P0 = b0 .* conj(b0);    % initial power of b
d0 = .22;               % initial desired sample

% Create and initialize an LMS lattice filter
[k,c,b,P,d,y,e]=init_lmslattice(L,k0,c0,b0,P0,d0);

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

ASPTLMSLATTICE, MODEL_ LMSLATTICE.