The optimal state estimation for competitive neural network with time-varying delay using Local Search Algorithm

In this paper, the optimal state estimation of competitive neural network with time-varying delay is investigated. A valid linear matrix inequality (LMI) method for neuron state estimation is proposed, sufficient conditions for the asymptotic stability of the error system are obtained. When the system is stable, further research is put forward based on the knowledge of cybernetics optimization. In particular, the Local Search Algorithm is used to optimize the parameters of state estimator. The optimal state estimator is obtained by minimizing the preset energy function. Numerical examples are included to illustrate the applicability of the proposed design method. (C) 2019 Elsevier B.V. All rights reserved.