Almost Periodic Solutions of Recurrent Neural Networks with State-Dependent and Structured Impulses

Date

2023-01-01

Author

Akhmet, Marat
Erim, Gülbahar

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The subject of the present paper is recurrent neural networks with variable impulsive moments. The impact activation functions are specified such that the structure for the jump equations are in full accordance with that one for the differential equation. The system studied in this paper covers the works done before, not only because the impacts have recurrent form, but also impulses are not state-dependent. The conditions for existence and uniqueness of asymptotically stable discontinuous almost periodic solutions are obtained. Through the present study, the possibility of neuron membranes with negative capacitance is involved in neural networks and this is one of the main novelties of the present study. The vector-matrix representation of the system is used for the clarity of the proofs and for making calculations easier.

Subject Keywords

Asymptotic stability, B-equivalence method, Discontinuous almost periodic motions, Neural networks with negative/, Positive capacitance, Recurrent impulsive neural networks, Recurrently structured impacts

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85145900962&origin=inward
https://hdl.handle.net/11511/102273

Journal

Discontinuity, Nonlinearity, and Complexity

DOI

https://doi.org/10.5890/dnc.2023.03.011

Collections

Department of Mathematics, Article

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Citation Formats

M. Akhmet and G. Erim, “Almost Periodic Solutions of Recurrent Neural Networks with State-Dependent and Structured Impulses,” Discontinuity, Nonlinearity, and Complexity, vol. 12, no. 1, pp. 141–165, 2023, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85145900962&origin=inward.