Global exponential stability of neural networks with non-smooth and impact activations

Date

2012-10-01

Author

Akhmet, Marat

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In this paper, we consider a model of impulsive recurrent neural networks with piecewise constant argument. The dynamics are presented by differential equations with discontinuities such as impulses at fixed moments and piecewise constant argument of generalized type. Sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are obtained. By employing Green's function we derive new result of existence of the periodic solution. The global exponential stability of the solution is investigated. Examples with numerical simulations are given to validate the theoretical results.

Subject Keywords

Recurrent neural networks, Impulsive differential equation, Piecewise constant argument, Equilibrium, Periodic solution, Global exponential stability

URI

https://hdl.handle.net/11511/35590

Journal

NEURAL NETWORKS

DOI

https://doi.org/10.1016/j.neunet.2012.06.004

Collections

Department of Mathematics, Article

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Citation Formats

M. Akhmet, “Global exponential stability of neural networks with non-smooth and impact activations,” NEURAL NETWORKS, pp. 18–27, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35590.