Statistical Mechanics of Temporal Association in Neural Networks

Part of Advances in Neural Information Processing Systems 3 (NIPS 1990)

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Andreas Herz, Zhaoping Li, J. van Hemmen


We study the representation of static patterns and temporal associa(cid:173) tions in neural networks with a broad distribution of signal delays. For a certain class of such systems, a simple intuitive understanding of the spatia-temporal computation becomes possible with the help of a novel Lyapunov functional. It allows a quantitative study of the asymptotic network behavior through a statistical mechanical analysis. We present analytic calculations of both retrieval quality and storage capacity and compare them with simulation results.