State estimation for static neural networks with time-varying delay

This paper is concerned with the state estimation problem for a class of static neural networks with time-varying delay Here the time derivative of the time-varying delay is no longer required to be smaller than one A delay partition approach is proposed to derive a delay-dependent condition under which the resulting error system is globally asymptotically stable The design of a desired state estimator for such kinds of delayed neural networks can be accomplished by means of solving a linear matrix inequality A simulation example is finally given to show the application of the developed approach (C) 2010 Elsevier Ltd All rights reserved