Please use this identifier to cite or link to this item:
|Title:||Delay-dependent state estimation for delayed neural networks|
|Authors:||He, Y. |
Linear matrix inequality (LMI)
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Nov 13, 2018
WEB OF SCIENCETM
checked on Nov 5, 2018
checked on Oct 27, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.