A perspective on graph theory-based stability analysis of impulsive stochastic recurrent neural networks with time-varying delays

A perspective on graph theory-based stability analysis of impulsive stochastic recurrent neural networks with time-varying delays

Abstract In this work, the exponential stability problem of impulsive recurrent neural networks is investigated; discrete time delay, continuously distributed delay and stochastic noise are simultaneously taken into consideration. In order to guarantee the exponential stability of our considered rec...

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Bibliographic Details
Main Authors: M. Iswarya, R. Raja, G. Rajchakit, J. Cao, J. Alzabut, C. Huang
Format: Article
Language:English
Published: SpringerOpen 2019-12-01
Series:Advances in Difference Equations
Subjects:
Recurrent neural networks (RNNs)
Exponential stability
Graph theory
Young’s inequality
Discrete time-varying delays
Infinite distributed time-varying delays
Online Access:https://doi.org/10.1186/s13662-019-2443-3

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