Please use this identifier to cite or link to this item: https://doi.org/10.1109/TENCON.2005.301253
Title: Robust stability analysis of delayed neural networks with polytopic type uncertainties
Authors: He, Y. 
Wang, Q.-G. 
Zheng, W.X.
Keywords: Delayed neural networks
Global robust stability
Linear matrix inequality (LMI)
Parameter-dependent Lyapunov functional
Polytopic type uncertainties
Issue Date: 2007
Citation: He, Y.,Wang, Q.-G.,Zheng, W.X. (2007). Robust stability analysis of delayed neural networks with polytopic type uncertainties. IEEE Region 10 Annual International Conference, Proceedings/TENCON 2007 : -. ScholarBank@NUS Repository. https://doi.org/10.1109/TENCON.2005.301253
Abstract: We investigate the problem of global robust stability for delayed neural networks in this paper. We first utilize the free-weighting matrices to express the relationship between the terms in the system equation, and then apply the S-procedure to derive a stability condition for delayed neural networks. Next, we extend this result so as to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. Finally, we demonstrate the usefulness of the obtained global robust stability criterion and its improvement over the existing results by using a numerical example given in [21] for interval delayed neural networks.
Source Title: IEEE Region 10 Annual International Conference, Proceedings/TENCON
URI: http://scholarbank.nus.edu.sg/handle/10635/71690
ISBN: 0780393112
DOI: 10.1109/TENCON.2005.301253
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