Delay-dependent state estimation for delayed neural networks

Please use this identifier to cite or link to this item: https://doi.org/10.1109/TNN.2006.875969

Title:	Delay-dependent state estimation for delayed neural networks
Authors:	He, Y. Wang, Q.-G. Wu, M. Lin, C.
Keywords:	Delay-dependent Linear matrix inequality (LMI) Neural networks State estimation
Issue Date:	Jul-2006
Citation:	He, Y., Wang, Q.-G., Wu, M., Lin, C. (2006-07). Delay-dependent state estimation for delayed neural networks. IEEE Transactions on Neural Networks 17 (4) : 1077-1081. ScholarBank@NUS Repository. https://doi.org/10.1109/TNN.2006.875969
Abstract:	In this letter, the delay-dependent state estimation problem for neural networks with time-varying delay is investigated. A delay-dependent criterion is established to estimate the neuron states through available output measurements such that the dynamics of the estimation error is globally exponentially stable. The proposed method is based on the free-weighting matrix approach and is applicable to the case that the derivative of a time-varying delay takes any value. An algorithm is presented to compute the state estimator. Finally, a numerical example is given to demonstrate the effectiveness of this approach and the improvement over existing ones. © 2006 IEEE.
Source Title:	IEEE Transactions on Neural Networks
URI:	http://scholarbank.nus.edu.sg/handle/10635/55518
ISSN:	10459227
DOI:	10.1109/TNN.2006.875969
Appears in Collections:	Staff Publications

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