Article ID Journal Published Year Pages File Type
408447 Neurocomputing 2011 5 Pages PDF
Abstract

The state estimation problem is studied in this paper for a class of recurrent neural networks with time-varying delay. A novel delay partition approach is developed to derive a delay-dependent condition guaranteeing the existence of a desired state estimator for the delayed neural networks. The design of the gain matrix of the state estimator can be achieved by solving a linear matrix inequality, where no slack variable is involved. A numerical example is finally provided to show the advantage of the proposed approach over some existing results.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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