ASSOCIATIVE MEMORY USING SYNCHRONIZATION IN A CHAOTIC NEURAL NETWORK

Z. Tan () and M. K. Ali ()
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Z. Tan: Department of Physics, The University of Lethbridge, 4401 University Dr. W. Lethbridge, Alberta T1K 3M4, Canada
M. K. Ali: Department of Physics, The University of Lethbridge, 4401 University Dr. W. Lethbridge, Alberta T1K 3M4, Canada

International Journal of Modern Physics C (IJMPC), 2001, vol. 12, issue 01, 19-29

Abstract: Synchronization is introduced into a chaotic neural network model to discuss its associative memory. The relative time of synchronization of trajectories is used as a measure of pattern recognition by chaotic neural networks. The retrievability of memory is shown to be connected to synapses, initial conditions and storage capacity. The technique is simple and easy to apply to neural systems.

Keywords: Chaos; Pattern Recognition; Associative Memory; Neural Networks (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1142/S0129183101001407

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