The attractors in sequence processing neural networks

Yong Chen, Ying Hai Wang, Kong Qing Yang

Published 2002-09-12Version 1

The average length and average relaxation time of attractors in sequence processing neural networks are investigated. The simulation results show that a critical point of $\alpha $, the loading ratio, is found. Below the turning point, the average length is equal to the number of stored patterns; conversely, the ratio of length and numbers of stored patterns, grow with an exponential dependence $\exp (A\alpha) $. Moreover, we find that the logarithm of average relaxation time is only linearly associated with $\alpha $ and the turning point of coupling degree is located for examining robustness of networks.