Boolean Neuron

A playground of Boolean operations learned by a single neuron.

A neuron like this is a building block of artificial neural networks. In this simple form, it takes binary inputs (0 or 1), and produces binary output with a formula

\[h(\vec{x})=S(w_0x_0+w_1x_1+w_2x_2)\] \[S(t)=\frac{1}{1+e^{-t}}\]

Where S is a sigmoid function:

x₀ is always 1, and is used to apply “bias” weight w₀.

This simple neuron can learn basic Boolean operations:

	AND
	OR
	NOT (on first input)

Use the sliders to change weights, and train the neuron to these basic operations.