Pattern recognition with a pulsed neural network

Abstract

This paper describes pulse transmission (PT) neural networks and provides a series of analytical and experimental findings regarding their abilities to perform pattern-mapping and temporal integration. We show the synaptic equations and the frequency transfer characteristics of the synapses. A network is described that performs the Xor function via pulses and that amplifies its output rate by means of synchronous groups assemblies of units that fire or burst simult aneously. Another network is described that does coarse-grid pattern recognition with pulses. This network performs temporal integration of pattern fragments over a period of time, and recognizes patterns that are obscured by noisy but changing foreground objects. Similarity is shown between certain pulsed networks in frequency operating modes and particular configurations of recurrent networks. A general class of pulsed neural networks is described.