Multilayer Perceptron

As discussed earlier, a single perceptron is even incapable of approximating an XOR function. To overcome this limitation, multiple perceptrons are stacked together as MLPs, where layers are connected as a directed graph. This way, the signal propagates one way, from input layer to hidden layers to output layer, as shown in the following diagram:

An MLP architecture having an input layer, two hidden layers, and an output layer

Fundamentally, an MLP is one the most simple FFNNs having at least three layers: an input layer, a hidden layer, and an output layer. An MLP was first trained with a backpropogation algorithm in the 1980s.