Title :
Delay-dependent state estimation for delayed neural networks
Author :
Yong He ; Qing-Guo Wang ; Min Wu ; Chong Lin
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
fDate :
7/1/2006 12:00:00 AM
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.
Keywords :
asymptotic stability; delays; matrix algebra; neural nets; state estimation; time-varying systems; delay-dependent state estimation problem; delayed neural networks; estimation error; free-weighting matrix; global exponential stability; time-varying delay; Delay effects; Delay estimation; Estimation error; Helium; Information science; Linear matrix inequalities; Neural networks; Neurons; Signal processing algorithms; State estimation; Delay-dependent; linear matrix inequality (LMI); neural networks; state estimation;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2006.875969