Neural Circuits and Parallel Implementation

Abstract

Hardware technologies for implementing neural networks can be either analog or digital. Analog hardware is a good choice. The design of analog chips requires good theoretical knowledge of transistor physics as well as experience. Weights in a neural network can be coded by one single analog element (e.g., a resistor). Very simple rules such as Kirchoff’s laws can be used to carry out addition of input signals. As an example, Boltzmann machines can be easily implemented by amplifying the natural noise present in analog devices.