THE ATTRACTORS IN SEQUENCE PROCESSING NEURAL NETWORKS

Yong Chen (), Yin Hai Wang and Kong Qing Yang
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Yong Chen: Physics Department of Lanzhou University, China (730000), China
Yin Hai Wang: Physics Department of Lanzhou University, China (730000), China
Kong Qing Yang: Physics Department of Lanzhou University, China (730000), China

International Journal of Modern Physics C (IJMPC), 2000, vol. 11, issue 01, 33-39

Abstract: 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 α, 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 dependenceexp(Aα). Moreover, we find that the logarithm of average relaxation time is only linearly associated with α and the turning point of coupling degree is located for examining robustness of networks.

Keywords: Neural Network; Asymmetric Neural Networks; Attractor; Relaxation Time; Dilution Factor (search for similar items in EconPapers)
Date: 2000
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DOI: 10.1142/S0129183100000043

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