8 plot_ invmodel

Purpose

Displays the optimal filter and the solution achieved by the adaptive filter for evaluating the adaptive inverse modeling (equalization) applications.

Syntax

plot_invmodel(w,h,e,D)

Description

plot_invmodel() is helpful in the verification stage in adaptive inverse modeling (equalization) applications. plot_invmodel() takes as input the adaptive filter coefficients vector $w(n)$, the transfer function to be inverted $h$, the mean square error vector $e(n)$ (that is usually returned by update_ipwin()), and the modeling delay $D$, and returns after rendering the graph. The variables of plot_invmodel() are summarized below.

 
Input variables:
  w : adaptive filter coefficients vector
  h : impulse response of the channel to be equalized
  e : mean square error vector
  D : modeling delay in the desired response path.

Example

Figure 9.7: The inverse modeling (equalizer) graph window.

An example graph window generated using plot_invmodel() is shown in Fig. 9.7. The top left panel shows the impulse response of the optimal solution $w_{opt}$ which is the inverse of the channel response $h$ in the sense that the convolution $w_{opt} * h$ results in a delayed impulse $\delta(n-D)$. The frequency response of this optimal solution is plotted in the middle left panel. The top two right panels show the impulse response and frequency response of the adaptive model. The bottom panel displays the evolution of the mean square error with time.