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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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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.