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28-09-2022

Global Exponential Stability of Inertial Cohen–Grossberg Neural Networks with Time-Varying Delays via Feedback and Adaptive Control Schemes: Non-reduction Order Approach

Authors: Sunny Singh, Umesh Kumar, Subir Das, Jinde Cao

Published in: Neural Processing Letters

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Abstract

In this article, the problem is dealt for the global exponential stability of delayed Cohen–Grossberg inertial neural networks (CGINNs) by constructing a new innovative Lyapunov functional instead of the traditional reduced-order method. The newly constructed Lyapunov functional together with two different control schemes and the inequality technique, analyze the global exponential stability for the considered second-order inertial neural networks (INNs). The dynamical behavior of CGINNs in the present study is new and different from the reduced-order method through variable substitution. The simpler inequalities in the proposed method help to achieve the stability criteria of CGINNs in a easier way as compared to the existing results. Finally, a numerical example is presented to validate the efficiency of the proposed method.
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Metadata
Title
Global Exponential Stability of Inertial Cohen–Grossberg Neural Networks with Time-Varying Delays via Feedback and Adaptive Control Schemes: Non-reduction Order Approach
Authors
Sunny Singh
Umesh Kumar
Subir Das
Jinde Cao
Publication date
28-09-2022
Publisher
Springer US
Published in
Neural Processing Letters
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-022-11044-9