Some generalized global stability criteria for delayed Cohen-Grossberg neural networks of neutral-type.

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ID: 57019
2019
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Ranked #33 of 55 articles by views in neural networks : the official journal of the international neural network society

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Abstract
This paper carries out a theoretical investigation into the stability problem for the class of neutral-type Cohen-Grossberg neural networks with discrete time delays in states and discrete neutral delays in time derivative of states. By employing a more general type of suitable Lyapunov functional, a set of new generalized sufficient criteria are derived for the global asymptotic stability of delayed neural networks of neutral-type. The proposed stability criteria are independently of the values of the time delays and neutral delays, and they completely rely on some algebraic mathematical relationships involving the values of the elements of the interconnection matrices and the other network parameters. Therefore, it is easy to verify the validity of the obtained results by simply using some algebraic equations representing the stability conditions. A detailed comparison between our proposed results and recently reported corresponding stability results is made, proving that the results given in this paper generalize previously published stability results. A constructive numerical example is also given to demonstrate the applicability of the results of the paper.
Reference Key
samli2019someneural Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Samli, Ruya;Senan, Sibel;Yucel, Eylem;Orman, Zeynep;
Journal neural networks : the official journal of the international neural network society
Year 2019
DOI
S0893-6080(19)30129-7
URL
Keywords
delayed neural networks lyapunov stability analysis matrix theory neutral systems

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