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

Zhicheng Shi, Yongqing Yang, Qi Chang and Xianyun Xu

Physica A: Statistical Mechanics and its Applications, 2020, vol. 540, issue C

Abstract: 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.

Keywords: Competitive neural network; Sampling state estimation; LMI; Optimal state estimator (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:540:y:2020:i:c:s0378437119317509

DOI: 10.1016/j.physa.2019.123102

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