Abstract
In this paper, the problem on global dissipativity is investigated for neural networks with time-varying delays and leakage delay as well as generalized activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and using linear matrix inequality (LMI) technique, a new delay-dependent criterion for checking the global dissipativity of the addressed neural networks is established in terms of LMIs, which can be checked numerically using the effective LMI toolbox in MATLAB. The proposed dissipativity criterion does not require the monotonicity of the activation functions and the differentiability of the time-varying delays, which means that our result generalizes and further improves those in the earlier publications.
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Zhao, Z., Song, Q. (2012). Global Dissipativity of Neural Networks with Time-Varying Delay and Leakage Delay. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_37
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DOI: https://doi.org/10.1007/978-3-642-31346-2_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31345-5
Online ISBN: 978-3-642-31346-2
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