% Copyright 1997 by Peter C. Jones and Scott D. Tepavich.
% All Rights Reserved.
%
% Learning mode

load th250.mat % Load the simulink signals (ThD, ThOut)

imax = length(t); % don't count too high in time... =)
e_sq = zeros(imax,1); %initialize error to 0

W = rand(30,1)*2 - 1.0;
mu = .1;
KEEPGOING=1;
loopcount = 0;
lEpoch = length(ThD), % data points in one epoch

while KEEPGOING
    i = rem( loopcount, imax ) + 1;
    loopcount = loopcount + 1;

  % 2
    x = 0*W;  % get an "input" array, initialized to 0, same size as W
    lW = length(W);
    if( i>lW )
      x(1:lW) = ThOut(i:-1:i-lW+1);
    else
      x(1:i) = ThOut(i:-1:1);
    end
    if(length(x)>lW), break, end
    ThC = sum( x .* W );

  % 3. Error = desired - actual
    delta = ThD(i) - ThC;
    e_sq(i) = delta^2; % sqared error

  % 4. Change weights
    Wnew = W + 2 * mu * delta * x;
    W = Wnew;

  % 5. plot J = fn(loop count), and compare
  if( rem(loopcount,lEpoch)==0 )
    epoch = fix(loopcount/lEpoch);
    J(epoch) = sum(e_sq);    % sum-squared-error
    if( rem(epoch,5)==0 ), figure(1), loglog(1:epoch, J(1:epoch)), end
    if( epoch == 10 ), pi, end
    if( log10(epoch) == floor(log10(epoch)) ), J(epoch), end
  end
  if( (J(epoch)<.0001) & (loopcount>imax) ), KEEPGOING=0; end
end; % end "while KEEPGOING"
loglog(1:epoch, J(1:epoch))
epoch