Threshold Logic Units

Abstract

The description of biological neural networks in the preceding chapter makes it natural to model neurons as threshold logic units: if a neuron receives enough excitatory input that is not compensated by equally strong inhibitory input, it becomes active and sends a signal to other neurons. Such a model was already examined very early in much detail by McCulloch and Pitts (1943) (Bull. Math. Biophys. 5115–133, 1943). As a consequence, threshold logic units are also known as McCulloch–Pitts neurons. Another name which is commonly used for a threshold logic unit is perceptron, even though the processing units that (Rosenblatt 1958) (Psychol. Rev. 65:386–408, 1958), (Rosenblatt 1962) (Rosenblatt, Principles of Neurodynamics, 1962) called “perceptrons” are actually somewhat more complex than simple threshold logic units.