# OR

input = [-1 0 0; -1 0 1; -1 1 0; -1 1 1];
desired_out = [-1; 1; 1; 1];
number_of_inputs = rows(input);

bias = -1;
coeff = 0.05;

# Get weights between -0.5 and 0.5
weights = rand(3,1) .- 0.5;

iterations = 10000;

out = zeros(4,1);

for i = 1:iterations
    for j = 1:number_of_inputs
    	h = input(j,:) * weights;
    	out(j) = sign(h);
        delta = desired_out(j) - out(j);

        # Update weights -> Wnew = Wold + DeltaW
        for k = 1:3
        	weights(k,1) = weights(k, 1) + coeff * delta * input(j, k);
        end
    end
end

disp(out);

# AND

input = [-1 0 0; -1 0 1; -1 1 0; -1 1 1];
desired_out = [-1; -1; -1; 1];
number_of_inputs = rows(input);

bias = -1;
coeff = 0.05;

# Get weights between -0.5 and 0.5
weights = rand(3,1) .- 0.5;

iterations = 10000;

out = zeros(4,1);

for i = 1:iterations
    for j = 1:number_of_inputs
        h = input(j,:) * weights;
        out(j) = sign(h);
        delta = desired_out(j) - out(j);

        # Update weights -> Wnew = Wold + DeltaW
        for k = 1:3
            weights(k,1) = weights(k, 1) + coeff * delta * input(j, k);
        end
    end
end

disp(out);