Abstract
In this paper, the global robust stability problem of delayed Takagi–Sugeno fuzzy Hopfield neural networks with discontinuous activation functions (TSFHNNs) is considered. Based on Lyapunov stability theory and M-matrices theory, we derive a stability criterion to guarantee the global robust stability of TSFHNNs. Compared with the existing literature, we remove the assumptions on the neuron activations such as Lipschitz conditions, bounded, monotonic increasing property or the assumption that the right-limit value is bigger than the left one at the discontinuous point. Finally, two numerical examples are given to show the effectiveness of the proposed stability results.
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Acknowledgments
This work was supported by National Natural Science Foundation of China (10771055, 60775047, 60835004), and National High Technology Research and Development Program of China (863 Program: 2007AA04Z244, 2008AA04Z214), Graduate Innovation Foundation of Hunan Province (2010).
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Wu, X., Wang, Y., Huang, L. et al. Robust stability analysis of delayed Takagi-Sugeno fuzzy Hopfield neural networks with discontinuous activation functions. Cogn Neurodyn 4, 347–354 (2010). https://doi.org/10.1007/s11571-010-9123-z
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DOI: https://doi.org/10.1007/s11571-010-9123-z