Statistical Mechanics of Temporal Association in Neural Networks
Abstract
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.
Cite
Text
Herz et al. "Statistical Mechanics of Temporal Association in Neural Networks." Neural Information Processing Systems, 1990.Markdown
[Herz et al. "Statistical Mechanics of Temporal Association in Neural Networks." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/herz1990neurips-statistical/)BibTeX
@inproceedings{herz1990neurips-statistical,
title = {{Statistical Mechanics of Temporal Association in Neural Networks}},
author = {Herz, Andreas V. M. and Li, Zhaoping and van Hemmen, J. Leo},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {176-182},
url = {https://mlanthology.org/neurips/1990/herz1990neurips-statistical/}
}