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Complex in a Simple Delayed Discrete Neural Network

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Abstract (2. Language): 
In this paper, we show that a delayed discrete Hopfield neural net- work of two identical neurons with no self-connections can demonstrate chaotic behavior away from the origin. To this end, we first trans- form the model, by a novel way, into an equivalent system which enjoys some nice properties, and construct chaotic invariant sets of this sys- tem such that the dynamics is conjugate to the shift with two symbols. This is complementary to the results in Huang and Zou (J. Nonlinear Sci.,15(2005), 291-303), where it was shown that the same system can have chaotic behavior near the origin.
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