Consideration of multiplexing in neural network hardware

This paper presents the results of research into a scheme for overcoming the communications `bottleneck´ within hardware neural networks, utilising frequency division multiplexing of amplitude modulated neural signals. The introduction explains the problem of connectivity in neural networks and the need for multiplexing, followed by an introduction to the FDM solution. A comparison of FDM with TDM is then presented which shows that it is necessary to allow a moderate amount of band overlap in the FDM channel, to utilise the available bandwidth effectively. This approach is possible by virtue of the inherent error tolerance of the neural system