Energy-efficient H∞

Dan Zhang; Wenjian Cai; Qing Guo Wang

doi:10.1016/j.sigpro.2014.01.032

Energy-efficient ^H∞

Dan Zhang
, Wenjian Cai
, Qing Guo Wang

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

16 Citations (Scopus)

Abstract

This paper is concerned with the energy-efficient filtering for a class of wireless sensor networks (WSNs). Due to the power limitation of WSNs, the measurement signal is transmitted to the remote filter infrequently and stochastically. A stochastic framework is proposed to formulate the filtering problem for such systems. A sufficient condition is established such that the filtering error system is mean-square stable and achieves a prescribed disturbance attenuation level in the ^H∞

Original language	English
Pages (from-to)	134-141
Number of pages	8
Journal	Signal Processing
Volume	101
DOIs	https://doi.org/10.1016/j.sigpro.2014.01.032
Publication status	Published - Aug 2014
Externally published	Yes

Keywords

Energy-efficient

ASJC Scopus subject areas

Control and Systems Engineering
Software
Signal Processing
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

Access to Document

10.1016/j.sigpro.2014.01.032

Cite this

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title = "Energy-efficient H∞",

abstract = "This paper is concerned with the energy-efficient filtering for a class of wireless sensor networks (WSNs). Due to the power limitation of WSNs, the measurement signal is transmitted to the remote filter infrequently and stochastically. A stochastic framework is proposed to formulate the filtering problem for such systems. A sufficient condition is established such that the filtering error system is mean-square stable and achieves a prescribed disturbance attenuation level in the H∞",

keywords = "Energy-efficient",

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year = "2014",

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AB - This paper is concerned with the energy-efficient filtering for a class of wireless sensor networks (WSNs). Due to the power limitation of WSNs, the measurement signal is transmitted to the remote filter infrequently and stochastically. A stochastic framework is proposed to formulate the filtering problem for such systems. A sufficient condition is established such that the filtering error system is mean-square stable and achieves a prescribed disturbance attenuation level in the H∞

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