📄 update_ipwin.m
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% [E,stop,brk] = update_ipwin(E,e,d,wp,x1,x2,x3,x4,x5)
%
% Updates the iteration progress window.
%
% Input variable
% E : Learning curve vector
% e : new error sample (column vector for block processing)
% d : new desired sample (column vector for block processing)
% wp : plot generated when the plot button is pressed, must be
% 'm' = plot_model is called to generate a prediction graph
% 'p' = plot_predict is called to generate a modeling graph
% 'a' = plot_anvc is called to generate an ANVC graph
% 'e' = plot_echo is called to generate an echo canceler graph
% 'b' = plot_beam is called to generate a beam former graph
% 'l' = plot_ale is called to generate an ALE graph
% 'i' = plot_invmodel is called to generate an inverse modeling graph
% x1-x5: parameters passed to the plot_xxx functions
%
% Output variables
% E : updated learning curve vector
% stop : control flag [0 = continue, 1 = stop]
% brk : flag for breaking out of processing loop
%
% NOTE : UPDATE_IPWIN uses the following global variables
% stop k_ des_ err_ pltf brk ipw
% Author : John Garas PhD.% Version 2.1, Release October 2002.% Copyright (c) DSP ALGORITHMS 2000-2002.
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