New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type
Author
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-16
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This research work conducts an investigation of the stability issues of neutral-type Cohen–Grossberg neural network models possessing discrete time delays in states and discrete neutral delays in time derivatives of neuron states.
By setting a new generalized appropriate Lyapunov functional candidate, some novel sufficient conditions are proposed for global asymptotic stability for the considered neural networks of neutral type.
This paper exploits some basic properties of matrices in the derivation of the results that establish a set of algebraic mathematical relationships between network parameters of this neural system.
A key feature of the obtained stability criteria is to be independent from time and neutral delays.
Therefore, the derived results can be easily tested.
Moreover, a constructive numerical example is studied to check the verification of presented global stability conditions.
American Psychological Association (APA)
Faydasicok, Ozlem. 2020. New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1139986
Modern Language Association (MLA)
Faydasicok, Ozlem. New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1139986
American Medical Association (AMA)
Faydasicok, Ozlem. New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1139986
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139986