16 init_ rlslfpef

Purpose

Creates and initializes the variables required for the RLS Lattice Forward Prediction Error Filter.

Syntax

[ff,bb,fb,cf,b,y,e,kf,kb] = init_rlslfpef(L)
[ff,bb,fb,cf,b,y,e,kf,kb] = init_rlslfpef(L,ff0,bb0,fb0,cf0,b0)

Description

Figure 5.22: Block diagram of the forward prediction error filter.

The block diagram of the RLS-Lattice forward prediction error filter is shown in Fig. 5.22 while the details of the RLS lattice structure showing its internal variables can be seen in Fig. 5.19. A summary of those variables is given below.

Input Parameters [Size]:: 
  L   : number of predictor stages 
  ff0 : initial autocorr. of forward prediction error [Lx1]
  bb0 : initial autocorr. of backward prediction error [Lx1]
  fb0 : initial crosscorrelation of f and b [Lx1]
  cf0 : initial conversion factor [Lx1]
  b0  : initial vector of backward prediction error [L+1 x 1]

Output parameters [Default]::
  ff  : autocorr. of forward prediction error [.001*ones(L,1)]
  bb  : autocorr. of backward prediction error [.001*ones(L,1)]
  fb  : crosscorrelation of f and b [zeros]
  cf  : conversion factor [ones]
  b   : vector of backward prediction error [zeros]
  y   : Linear combiner output [zero]
  e   : Linear combiner error [rand]
  kf  : forward lattice coefficients [zeros]
  kb  : backward lattice coefficients [zeros]

Example

L  = 5;                 % Number of lattice stages 
ff = zeros(L,1);        % autocorr. for forward prediction error
bb = zeros(L,1);        % autocorr. for backward prediction error
fb = zeros(L,1);        % crosscorr. between f and b
cf = zeros(L,1);        % conversion factor
b  = zeros(L+1,1);      % backward prediction error 

% Create and initialize a lattice RLSLFPEF
[ff,bb,fb,cf,b,y,e,kf,kb] = init_rlslfpef(L,ff,bb,fb,cf,b);

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

ASPTRLSLFPEF, PREDICT_ RLSLFPEF.