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Global stability analysis of delayed complex-valued fractional-order coupled neural networks with nodes of different dimensions

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Abstract

In this paper, the delayed fractional-order complex-valued coupled neural networks (FCCNNs) with nodes of different dimensions are investigated. Firstly, stability theorems for linear fractional-order systems with multiple delays are presented. Secondly, by using the homeomorphism theory, the existence and uniqueness of the equilibrium point for delayed FCCNNs are proved. Then, the global stability criteria for delayed FCCNNs are derived by comparison theorem. Finally, numerical examples are given to illustrate the effectiveness of the presented results.

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Acknowledgements

The research is supported by grants from the National Natural Science Foundation of China (Nos. 61572233 and 11471083), the Fundamental Research Funds for the Central Universities (No. 21612443), and the Science and Technology Program of Guangzhou, China (No. 201707010404).

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  1. Department of Mathematics, Jinan University, Guangzhou, 510632, People’s Republic of China

    Manchun Tan & Qi Pan

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  1. Manchun Tan
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  2. Qi Pan
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Correspondence to Manchun Tan.

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Tan, M., Pan, Q. Global stability analysis of delayed complex-valued fractional-order coupled neural networks with nodes of different dimensions. Int. J. Mach. Learn. & Cyber. 10, 897–912 (2019). https://doi.org/10.1007/s13042-017-0767-4

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  • DOI: https://doi.org/10.1007/s13042-017-0767-4

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