Abstract
This paper investigates the problem of global asymptoticstability for a class of uncertain neural networks with time-varying and distributed delays. The uncertainties we considered in this paper are norm-bounded, and possibly time-varying. By Lyapunov-Krasovskii functional approach and S-procedure, a new stability criteria for the asymptotic stability of the system is derived in terms of linear matrix inequalities (LMIs). Two simulation examples are given to demonstrate the effectiveness of the developed techniques.
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© 2007 Springer-Verlag Berlin Heidelberg
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Qiu, J., Zhang, J., Gao, Z., Yang, H. (2007). New Global Asymptotic Stability Criterion for Uncertain Neural Networks with Time-Varying and Distributed Delays. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_101
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DOI: https://doi.org/10.1007/978-3-540-72383-7_101
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72382-0
Online ISBN: 978-3-540-72383-7
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