Abstract
The global exponential stability problem for a class of complex-valued recurrent neural networks with both asynchronous time-varying delays and impulse is concerned in this paper. By using Schur complement and Lyapunov functional, some new sufficient criteria to ascertain globally exponential stability of the equilibrium point are obtained in terms of linear matrix inequality. An example is given to illustrate the effectiveness of the results.
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Acknowledgments
This work was supported by the Excellent Doctor Innovation Program of Xinjiang University (Grant No. XJUBSCX-2015006), the Excellent Doctor Innovation Program of Xinjiang Uyghur Autonomous Region (Grant No. XJGRI2016001), the National Natural Science Foundation of People’s Republic of China (Grant No. 61164004).
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Zhang, D., Jiang, H., Hu, C., Yu, Z., Huang, D. (2017). Global Stability of Complex-Valued Neural Networks with Time-Delays and Impulsive Effects. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10636. Springer, Cham. https://doi.org/10.1007/978-3-319-70090-8_84
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DOI: https://doi.org/10.1007/978-3-319-70090-8_84
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