perceptron

Terms from Artificial Intelligence: humans at the heart of algorithms

The glossary is being gradually proof checked, but currently has many typos and misspellings.

The perceptron is the earliest kind of artificial neuron. It has a number of inputs and weights for each. In operation the inputs are multipled by the weights and summed to give an overall input activation. This is then compared with a threshold, and if the input activation exceeds the threshold, the perceptron fires. A simple percepttron arranged in a single layer cannot solve complex problems such as the XOR problem, but multi-layer perceptrons are harder to train. For many years this limited practical development of artificial neural networks until the adoption of non-linear threshold functons and the development of backpropagation.

Used in Chap. 6: pages 74, 75, 83, 84; Chap. 7: page 92; Chap. 8: pages 102, 103; Chap. 9: page 127

A single perceptron