j

.m source file about soft compute.

	% gradient checking for W1
	delta = 1e-8;
	num_dE_dW1 = zeros(size(W1));
	for j = 1:length(W1(:));
		new_W1 = W1;
		new_W1(j) = new_W1(j)+delta;
		new_X1 = tanh([X0 one]*new_W1);
		new_X2 = tanh([new_X1 one]*W2);
		new_diff = T - new_X2;	% error
		new_E = sum(sum(new_diff.^2));
		num_dE_dW1(j) = (new_E-E)/delta;
	end
%	tmp = max(max(abs(dE_dW1-num_dE_dW1)));
	error_leng = sqrt(sum((dE_dW1(:)-num_dE_dW1(:)).^2));
	grad_leng = sqrt(sum((dE_dW1(:)).^2));
	diff_W1(i) = error_leng/grad_leng;
	fprintf('===> Length of W1 grad error = %g (%.2g%%)\n', ...
		error_leng, error_leng/grad_leng*100);

	% gradient checking for W2
	num_dE_dW2= zeros(size(W2));
	for j = 1:length(W2(:));
		new_W2 = W2;
		new_W2(j) = new_W2(j)+delta;
		new_X1 = tanh([X0 one]*W1);
		new_X2 = tanh([new_X1 one]*new_W2);
		new_diff = T - new_X2;	% error
		new_E = sum(sum(new_diff.^2));
		num_dE_dW2(j) = (new_E-E)/delta;
	end
%	tmp = max(max(abs(dE_dW2-num_dE_dW2)));
	error_leng = sqrt(sum((dE_dW2(:)-num_dE_dW2(:)).^2));
	grad_leng = sqrt(sum((dE_dW2(:)).^2));
	diff_W2(i) = error_leng/grad_leng;
	fprintf('===> Length of W2 grad error = %g (%.2g%%)\n', ...
		error_leng, error_leng/grad_leng*100);