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Discrete-time dynamics of coupled quasi-periodic and chaotic neural network oscillators

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1 Author(s)
X. Wang ; Dept. of Math., Univ., of Southern California, Los Angeles, CA, USA

An analytical and computational study of the collective behavior of coupled discrete-time neural network oscillators is presented, with special emphasis on the oscillators being quasi-periodic and chaotic through the Hopf bifurcation and period-doubling bifurcations as the neuron gain is varied. The effects of various coupling structures on the dynamic features like frequency locking, amplitude death, and spatiotemporal chaos, which are interesting to neural information processing such as stimulus-dependent synchronization and pattern formation, are investigated

Published in:

Neural Networks, 1992. IJCNN., International Joint Conference on  (Volume:3 )

Date of Conference:

7-11 Jun 1992