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Associative dynamics in a chaotic neural network. (English) Zbl 1423.68396

Summary: An associative network is constructed with chaotic neuron models interconnected through a conventional auto-associative matrix of synaptic weights. The associative dynamics of the network is analysed with spatio-temporal output patterns, quasi-energy function, distances between internal state vectors and orbital instability. The network shows a periodic response after a nonperiodic transient phase when the external stimulations are spatially constant. The retrieval characteristics and the duration in the transient phase are dependent on the initial conditions. The results imply that the transient dynamics can be interpreted as a memory searching process. The network also shows periodic responses with short and very long periods when external stimulations are not spatially constant, but corresponding to a stored pattern and an unstored pattern, respectively. The responses to the external stimulations can be utilized for a pattern recognition with nonlinear dynamics.

MSC:

68T10 Pattern recognition, speech recognition
37D45 Strange attractors, chaotic dynamics of systems with hyperbolic behavior
92B20 Neural networks for/in biological studies, artificial life and related topics
Full Text: DOI

References:

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