A digital neuron realization for the random neural network model

Abstract

In this study the neuron of the random neural network (RNN) model (Gelenbe 1989) is designed using digital circuitry. In the RNN model, each neuron accumulates arriving pulses and can fire if its potential at a given instant of time is strictly positive. Firing occurs at random, the intervals between successive firing instants following an exponential distribution of constant rate. When a neuron fires, it routes the generated pulses to the appropriate output lines in accordance with the connection probabilities. In the digital circuitry the fundamental parts of the neuron are simulated by realizing Input Module, Neuron Potential Module, Firing Module and Routing Module. The neuron potential module accumulates incoming signals collected by the input Module at the input site. The Firing Module generates random pulses with an exponential distribution of fixed rate. The pulses generated by the firing Module are distributed to the other neurons through the Routing Module at the output side. A network of neurons can be constructed by using the digital circuitry presented for the single neuron. All the parts of the random neuron circuit are simulated by using Circuitmaker and Pspice digital simulation packages and the neuron is realized digitally by using LS-TTL IC's.