Abstract
This paper deals with the problem of state estimation for discretestochastic recurrent neural network with interval time-delays. The activationfunctions are assumed to be globally Lipschitz continuous. Attention is focusedon the design of a state estimator which ensures the global stability of theestimation error dynamics. A delay-dependent condition with dependence on theupper and lower bounds of the delays is given in terms of a linear matrixinequality (LMI) to solve the neuron state estimation problem. When this LMI isfeasible, the expression of a desired state estimator is also presented. Inaddition, slack matrices are introduced to reduce the conservatism of thecondition. A numerical example is provided to demonstrate the applicability ofthe proposed approach. ICIC International
Original language | English |
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Pages (from-to) | 465-470 |
Number of pages | 6 |
Journal | ICIC Express Letters |
Volume | 3 |
Issue number | 3 |
Publication status | Published - 2009 Sep 1 |
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Control and Systems Engineering