learbpm

clear all
close all
format compact
nntwarn off

P = -1:0.1:-0.5;
T = [-.9602 -.5770 -.0729 .3771 .6405 .6600];

[R, Q] = size(P);
[S3,Q] = size(T);
S1 = 7;
S2 = 7;
[W1, B1] = nwtan(S1, R);
[W2, B2] = nwtan(S2, S1);
[W3, B3] = rands(S3, S2);

load wagi %zaladowanie wag zapisanych poprzednio w learnbp

A1 = tansig(W1 * P, B1);
A2 = tansig(W2 * A1, B2);
A3 = purelin(W3 * A2, B3);
E = T - A3;

disp_freq = 100;
max_epoch = 10000;
err_goal = 0.001;
lr = 0.001;
error = [];
mc = 0.99; % 0.1 - 0.9, 0.95, 0.99
SSE = sumsqr(E);
%inicjalizowanie poprzednich wag
dW1 = zeros(size(W1));
dW2 = zeros(size(W2));
dW3 = zeros(size(W3));
dB1 = zeros(size(B1));
dB2 = zeros(size(B2));
dB3 = zeros(size(B3));

for epoch= 1 : max_epoch
    if SSE < err_goal, epoch=epoch-1;
        epoch
        SSE
        break
    end

    D3 = deltalin(A3, E);
    D2 = deltatan(A2, D3, W3);
    D1 = deltatan(A1, D2, W2);

    [dW1, dB1] = learnbpm(P, D1, lr, mc, dW1, dB1);
    [dW2, dB2] = learnbpm(A1, D2, lr, mc, dW2, dB2);
    [dW3, dB3] = learnbpm(A2, D3, lr, mc, dW3, dB3);

    W1 = W1 + dW1;
    B1 = B1 + dB1;
    W2 = W2 + dW2;
    B2 = B2 + dB2;
    W3 = W3 + dW3;
    B3 = B3 + dB3;

    A1 = tansig(W1 * P, B1);
    A2 = tansig(W2 * A1, B2);
    A3 = purelin(W3 * A2, B3);
    E = T - A3;
    SSE=sumsqr(E);
    error=[error SSE];
    if(rem(epoch,disp_freq)==0)
        epoch
        SSE
        plot(P, T, 'r', P, A3, 'g')
        pause(1e-100)
    end
end
epoch
SSE