create perceptron algorithm in matlab

main.m
% Initialize the data
X = [0 0 1; 0 1 1; 1 0 1; 1 1 1];
y = [0; 0; 0; 1];

% Initialize the weights
w = randn(size(X, 2), 1);

% Set the learning rate
alpha = 0.1;

% Perform the perceptron algorithm
for i = 1:1000
    % Choose a random data point
    idx = randi(size(X, 1));
    x_i = X(idx, :)';
    y_i = y(idx);

    % Compute the activation
    z_i = w'*x_i;
    a_i = 1/(1+exp(-z_i));

    % Update the weights
    d_w = alpha*(y_i-a_i)*a_i*(1-a_i)*x_i;
    w = w + d_w;
end

% Test the perceptron
X_test = [1 1 1; 1 0 1; 0 1 1; 0 0 1];
for i = 1:size(X_test, 1)
    x_i = X_test(i, :)';
    z_i = w'*x_i;
    a_i = 1/(1+exp(-z_i));
    fprintf('Input: %s\tOutput: %f\n', mat2str(x_i'), a_i);
end
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