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Delay-independent stability criteria for complex-valued BAM neutral-type neural networks with time delays

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Abstract

This paper focuses on the global asymptotic stability of complex-valued bidirectional associative memory (BAM) neutral-type neural networks with time delays. By virtue of homeomorphism theory, inequality techniques and Lyapunov functional, a set of delay-independent sufficient conditions is established for assuring the existence, uniqueness and global asymptotic stability of an equilibrium point of the considered complex-valued BAM neutral-type neural network model. The assumption on boundedness of the activation functions is not required, and the LMI-based criteria are easy to be checked and executed in practice. Finally, we give one example with simulation to show the applicability and effectiveness of our main results.

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Acknowledgements

The research is supported by Grants from the National Natural Science Foundation of China (Nos. 61572233 and 11471083) and the Science and Technology Program of Guangzhou, China (No. 201707010404).

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  1. College of Information Science, Jinan University, Guangzhou, 510632, China

    Desheng Xu & Manchun Tan

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  1. Desheng Xu
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  2. Manchun Tan
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Correspondence to Manchun Tan.

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Xu, D., Tan, M. Delay-independent stability criteria for complex-valued BAM neutral-type neural networks with time delays. Nonlinear Dyn 89, 819–832 (2017). https://doi.org/10.1007/s11071-017-3486-1

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