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Stability analysis of recurrent neural networks with piecewise constant argument of generalized type

✍ Scribed by M.U. Akhmet; D. Aruğaslan; E. Yılmaz

Publisher
Elsevier Science
Year
2010
Tongue
English
Weight
456 KB
Volume
23
Category
Article
ISSN
0893-6080

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✦ Synopsis

In this paper, we apply the method of Lyapunov functions for differential equations with piecewise constant argument of generalized type to a model of recurrent neural networks (RNNs). The model involves both advanced and delayed arguments. Sufficient conditions are obtained for global exponential stability of the equilibrium point. Examples with numerical simulations are presented to illustrate the results.

📜 SIMILAR VOLUMES

Global exponential stability of generali
Global exponential stability of generalized recurrent neural networks with discrete and distributed delays
✍ Yurong Liu; Zidong Wang; Xiaohui Liu 📂 Article 📅 2006 🏛 Elsevier Science 🌐 English ⚖ 159 KB

This paper is concerned with analysis problem for the global exponential stability of a class of recurrent neural networks (RNNs) with mixed discrete and distributed delays. We first prove the existence and uniqueness of the equilibrium point under mild conditions, assuming neither differentiability