The perceptron is the earliest kind of artificial neuron. It has a number of inputs and weights for each. In operation the iputs are multipled by the weights and summed to gib and input caruvation. This is then compared with a threshold function, and if the input activation exceeds the threshold, the perceptron fires. A simple percepttron arranged ina. single layer acnnot solve complex problems such as the XOR problem, but multi-layer perceptrons are hard to train. For many years this limited practicla developemnt of arificial neural networks until the adoption of non-linear threshold functons and the development backpropogation.
Used on pages 110, 122, 188
A single perceptron