Abstract
A class of coupled neural networks with nodes of different coupling time-delays and different state dimensions is investigated in this paper. Based on Lyapunov stability theory, some sufficient conditions for synchronization of coupled neural networks are derived. The coupling configuration matrix is not necessary to be symmetric or irreducible, and the inner coupling matrix need not be symmetric. Finally, numerical examples are presented to demonstrate the effectiveness of the designed method.
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Acknowledgments
The research is supported by grants from the National Natural Science Foundation of China (No.11471083 and No. 61572233), the Natural Science Foundation of Guangdong Province in China (No.9151001003000005), and the Fundamental Research Funds for the Central Universities (No. 21612443).
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Tan, M., Xu, D. (2016). Synchronization of Coupled Neural Networks with Nodes of Different Dimensions. In: Cheng, L., Liu, Q., Ronzhin, A. (eds) Advances in Neural Networks – ISNN 2016. ISNN 2016. Lecture Notes in Computer Science(), vol 9719. Springer, Cham. https://doi.org/10.1007/978-3-319-40663-3_16
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DOI: https://doi.org/10.1007/978-3-319-40663-3_16
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