Finite-Time Stability Criteria for a Class of High-Order Fractional Cohen–Grossberg Neural Networks with Delay
Joint Authors
Hu, Junhao
Yang, Zhanying
Mei, Jun
Zhang, Jie
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-09
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This paper focuses on a class of delayed fractional Cohen–Grossberg neural networks with the fractional order between 1 and 2.
Two kinds of criteria are developed to guarantee the finite-time stability of networks based on some analytical techniques.
This method is different from those in some earlier works.
Moreover, the obtained criteria are expressed as some algebraic inequalities independent of the Mittag–Leffler functions, and thus, the calculation is relatively simple in both theoretical analysis and practical applications.
Finally, the feasibility and validity of obtained results are supported by the analysis of numerical simulations.
American Psychological Association (APA)
Yang, Zhanying& Zhang, Jie& Hu, Junhao& Mei, Jun. 2020. Finite-Time Stability Criteria for a Class of High-Order Fractional Cohen–Grossberg Neural Networks with Delay. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1141542
Modern Language Association (MLA)
Yang, Zhanying…[et al.]. Finite-Time Stability Criteria for a Class of High-Order Fractional Cohen–Grossberg Neural Networks with Delay. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1141542
American Medical Association (AMA)
Yang, Zhanying& Zhang, Jie& Hu, Junhao& Mei, Jun. Finite-Time Stability Criteria for a Class of High-Order Fractional Cohen–Grossberg Neural Networks with Delay. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1141542
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141542