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Lyapunov approach to manifolds stability for impulsive Cohen-Grossberg-type conformable neural network models
Trayan Stamov1, Gani Stamov2, Ivanka Stamova2
1Department of Engineering Design, Technical University of Sofia, Sofia 1000, Bulgaria.
Abstract:
In this paper, motivated by the advantages of the generalized conformable derivatives, an impulsive conformable Cohen-Grossberg-type neural network model is introduced. The impulses, which can be also considered as a control strategy, are at fixed instants of time. We define the notion of practical stability with respect to manifolds. A Lyapunov-based analysis is conducted, and new criteria are proposed. The case of bidirectional associative memory (BAM) network model is also investigated. Examples are given to demonstrate the effectiveness of the established results.
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