New results on finite-time stability of fractional-order neural networks with time-varying delay-Reference-Cited by-同舟云学术

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New results on finite-time stability of fractional-order neural networks with time-varying delay

Published:2021-08-04 Issue:24 Volume:33 Page:17489-17496
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Thanh Nguyen T.,Niamsup P.,Phat Vu N.

Funder

national foundation for science and technology development

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-021-06339-2.pdf

Reference40 articles.

1. Forti F, Tesi A (1995) New conditions for global stability of neural networks with application to linear and quadratic programming problems, IEEE Trans Circuits Syst I Funda Theory Appl. 42(7), 354–366

2. Arik S (2002) An analysis of global asymptotic stability of delayed cellular neural networks. IEEE Trans. on Neural Netw. 3(5), 1239–1242

3. Gupta D, Cohn LF (2012) Intelligent transportation systems and NO2 emissions: Predictive modeling approach using artificial neural networks. J. Infrastruct. Syst. 18(2), 113–118

4. Phat VN, Fernando T, Trinh H (2014) Observer-based control for time-varying delay neural networks with nonlinear observation. Neural Computing and Applications 24:1639–1645

5. Abdelsalam SI, Velasco-Hernandez JX, Zaher A.Z. (2012) Electro-magnetically modulated self-propulsion of swimming sperms via cervical canal. Biomechanics and Modeling in Mechanobiology 20:861–878

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