Stochastic H∞ Filtering for Complex-valued Generalized Neural Networks with Brownian Motions and Time Delays

被引：0

作者：

Chen, Zhisheng ^{[1
]}

Liu, Daifei ^{[1
]}

机构：

[1] Changsha Univ Sci & Technol, Sch Energy & Power Engn, Changsha, Hunan, Peoples R China

来源：

2019 25TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC) | 2019年

基金：

中国国家自然科学基金;

关键词：

H-infinity filtering; complex-valued neural network; time delay system; Brownian motions; STABILITY ANALYSIS; SYSTEMS; INEQUALITY;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Robust filter design problem is investigated for complex-valued neural networks (CVNNs). Jensen inequality, improved reciprocally convex combination approach and Ito Isometry are applied to obtain a less conservative delay-dependent criterion via linear matrix inequalities (LMIs). Effectiveness of the proposed technique is demonstrated by a numerical example.

引用

页码：558 / 562

页数：5

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