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dc.contributor.authorStamov, Gani
dc.contributor.authorStamova, Ivanka
dc.contributor.authorMartynyuk, Anatoliy
dc.contributor.authorStamov, Trayan
dc.date.accessioned2021-04-19T15:18:41Z
dc.date.available2021-04-19T15:18:41Z
dc.date.issued3/15/2020
dc.identifierdoi: 10.3390/e22030337
dc.identifier.citationEntropy 22 (3): 337 (2020)
dc.identifier.urihttps://hdl.handle.net/20.500.12588/483
dc.description.abstractIn this paper, a new class of impulsive neural networks with fractional-like derivatives is defined, and the practical stability properties of the solutions are investigated. The stability analysis exploits a new type of Lyapunov-like functions and their derivatives. Furthermore, the obtained results are applied to a bidirectional associative memory (BAM) neural network model with fractional-like derivatives. Some new results for the introduced neural network models with uncertain values of the parameters are also obtained.
dc.titleDesign and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks
dc.date.updated2021-04-19T15:18:41Z


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