Novel global polynomial stability criteria of impulsive complex-valued neural networks with multi-proportional delays-Reference-Cited by-同舟云学术

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Novel global polynomial stability criteria of impulsive complex-valued neural networks with multi-proportional delays

Published:2021-10-04 Issue:4 Volume:34 Page:2913-2924
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Zhang Yongkang,Zhou Liqun^ORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Tianjin City

Tianjin Normal University

the innovative talents cultivation of young middle aged backbone teachers of Tianjin

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-021-06555-w.pdf

Reference46 articles.

1. Kim T, Adali T (2003) Approximation by fully complex multilayer perceptrons. Neural Comput 15(7):1641–1666. https://doi.org/10.1162/089976603321891846

2. Nitta T (2004) Orthogonality of decision boundaries in complex-valued neural networks. Neural Comput 16(1):73–97. https://doi.org/10.1162/08997660460734001

3. Cha I, Kassam SA (1995) Channel equalization using adaptive complex radial basis function networks. IEEE J Sel Areas Commun 13(1):122–131. https://doi.org/10.1109/49.363139

4. Goh SL, Mandic DP (2007) An augmented extended kalman filter algorithm for complex-valued recurrent neural networks. Neural Comput 19(4):1039–1055. https://doi.org/10.1162/neco.2007.19.4.1039

5. Savitha R, Sundararajan S, Suresh N (2009) A fully complex-valued radial basis function network and its learning algorithm. Int J Neural Syst 19(4):253–267. https://doi.org/10.1142/S0129065709002026

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