L2 - L∞ filtering for time-delayed switched hopfield neural networks

Choon Ki Ahn; Moon Kyou Song

L₂ - L_∞ filtering for time-delayed switched hopfield neural networks

Research output: Contribution to journal › Article › peer-review

Abstract

This paper investigates the delay-dependent L₂ - L _∞ filtering problem for time-delayed switched Hopfield neural networks. A new type of L₂ - L_∞ filter is proposed such that the filtering error system is asymptotically stable with guaranteed L₂ - L_∞ performance. The criterion is formulated in terms of linear matrix inequalities (LMIs), which can be checked readily by using certain types of standard numerical packages. A numerical example illustrates the effectiveness of the proposed L₂ - L _∞ filter. ICIC International

Original language	English
Pages (from-to)	1831-1843
Number of pages	13
Journal	International Journal of Innovative Computing, Information and Control
Volume	7
Issue number	4
Publication status	Published - 2011 Apr
Externally published	Yes

Keywords

Hopfield neural networks
L - L filtering
Linear matrix inequality (LMI)
Lyapunov-Krasovskii stability theory
Switched systems

ASJC Scopus subject areas

Software
Theoretical Computer Science
Information Systems
Computational Theory and Mathematics

Cite this

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abstract = "This paper investigates the delay-dependent L2 - L ∞ filtering problem for time-delayed switched Hopfield neural networks. A new type of L2 - L∞ filter is proposed such that the filtering error system is asymptotically stable with guaranteed L2 - L∞ performance. The criterion is formulated in terms of linear matrix inequalities (LMIs), which can be checked readily by using certain types of standard numerical packages. A numerical example illustrates the effectiveness of the proposed L2 - L ∞ filter. ICIC International",

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AB - This paper investigates the delay-dependent L2 - L ∞ filtering problem for time-delayed switched Hopfield neural networks. A new type of L2 - L∞ filter is proposed such that the filtering error system is asymptotically stable with guaranteed L2 - L∞ performance. The criterion is formulated in terms of linear matrix inequalities (LMIs), which can be checked readily by using certain types of standard numerical packages. A numerical example illustrates the effectiveness of the proposed L2 - L ∞ filter. ICIC International

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KW - Linear matrix inequality (LMI)

KW - Lyapunov-Krasovskii stability theory

KW - Switched systems

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L₂ - L_∞ filtering for time-delayed switched hopfield neural networks

Abstract

Keywords

ASJC Scopus subject areas

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