Dynamical Learning of Neural Networks Based on Chaotic Dynamics

Abstract

This paper proposes a new dynamical memory system based on chaotic neural networks, and its learning scheme. It is demonstrated that, when no embedded pattern, i.e., unknown pattern, is applied to the system, the output pattern travels around the embedded patterns, and the traveling phases depend on a external parameter of the networks such as the input from the other neurons or cortex. Further, the temporal output of the networks re ects a hierarchical structure of the memorized patterns.

11 Figures and Tables

Cite this paper

@inproceedings{Ito1998DynamicalLO, title={Dynamical Learning of Neural Networks Based on Chaotic Dynamics}, author={Kazuki Ito}, year={1998} }