Function deep_learning_playground::perceptron::single::logical_perceptron

pub fn logical_perceptron<T: Float>(
    w1: &'static T, 
    w2: &'static T, 
    bias: &'static T
) -> Box<dyn Fn(bool, bool) -> bool>

logical_perceptron is the logical perceptron. It can generates some logical gates (and_perceptron, nand_perceptron, or_perceptron) and generate a function that passes the sum of weighted signals (\(b+X\cdot W\) where \(b\in\mathbb{R}\) is a bias value, \(W^{2\times 1}=\left(w_1,w_2\right)^T, X^{1\times 2}=\left(x_1,x_2\right)\) and \(w_1\) and \(w_2\) are weights of \(x_1\) and \(x_2\)) to the activation function.

Arguments

• w1 - Weights for signal x1
• w2 - Weights for signal x2
• bias - Bias that determines the ease of firing of neurons

e.g.

assert_eq!(true, deep_learning_playground::perceptron::single::logical_perceptron(&0.5, &0.5, &-0.7)(true, true));
assert_eq!(false, deep_learning_playground::perceptron::single::logical_perceptron(&-0.5, &-0.5, &0.7)(true, true));
assert_eq!(true, deep_learning_playground::perceptron::single::logical_perceptron(&0.5, &0.5, &-0.2)(true, false));