Geometry of phase space and asymptotic behavior for oscillatory neural networks

Halina V. Grushevskaja; George G. Krylov; Anatoly T. Vlassov

doi:10.1117/12.304824

25 March 1998 Geometry of phase space and asymptotic behavior for oscillatory neural networks

Halina V. Grushevskaja, George G. Krylov, Anatoly T. Vlassov

Proceedings Volume 3390, Applications and Science of Computational Intelligence; (1998) https://doi.org/10.1117/12.304824
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

The asymptotic expansions of the solutions within the framework of been found phase-space geometry for oscillatory neural model are constructed. The oscillatory neural networks consist of non-identical neurons are examined. The phenomenon of mutual neurons' synchronization has been analyzed.

Citation Download Citation

Halina V. Grushevskaja, George G. Krylov, and Anatoly T. Vlassov "Geometry of phase space and asymptotic behavior for oscillatory neural networks", Proc. SPIE 3390, Applications and Science of Computational Intelligence, (25 March 1998); https://doi.org/10.1117/12.304824

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