design the function function t_hat= perceptron_predict(x, map_func, theta). the function returns the perceptron output t_hat, as a column vector of hard predictions applied to inputs in matlab

The function perceptron_predict() in MATLAB can be designed as follows:

main.m
function t_hat = perceptron_predict(x, map_func, theta)
% perceptron_predict calculates the perceptron output as a column vector of hard predictions
% for a given input vector x, map function and theta.

% x: input vector
% map_func: the mapping function
% theta: a column vector of the perceptron weights

% Output:
% t_hat: predicted output value

% calculate the output value
output = map_func(theta' * x);

% binary hard prediction
if output >= 0.5
  t_hat = 1;
else
  t_hat = 0;
end
end
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Here, x is the input vector of the input layer, map_func is the mapping function used for the perceptron, and theta is the weight vector of the perceptron. The output value of the perceptron is calculated as the dot product of the input vector and weight vector along with the mapping function. The output is then classified as a 0 or 1 based on a threshold of 0.5. t_hat is the binary hard prediction returned by the function.

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