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

Complexity

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

Philosophy

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