On applying Haar wavelet to achieving better optimal estimation for a class of dynamic multiscale system

Peiling Cui; Quan Pan; Lei Zhang; Hongcai Zhang

On applying Haar wavelet to achieving better optimal estimation for a class of dynamic multiscale system

Peiling Cui, Quan Pan, Lei Zhang, Hongcai Zhang

自动化学院

Northwestern Polytechnical University Xian

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

A class of dynamic multiscale system (DMS) is dealt with. This paper aims to achieve a better optimal estimation for this class of DMS. A model and an algorithm for this class of DMS is presented. The Haar wavelet approach is described; the description mainly involves developing the state equation and augmenting the measurement equation. The optimal filtering outputs of coarse scales are determined. The simulation results show that the noise compression ratio at each scale obtained by our approach is much higher.

源语言	英语
页（从-至）	149-152
页数	4
期刊	Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
卷	22
期	2
出版状态	已出版 - 4月 2004

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abstract = "A class of dynamic multiscale system (DMS) is dealt with. This paper aims to achieve a better optimal estimation for this class of DMS. A model and an algorithm for this class of DMS is presented. The Haar wavelet approach is described; the description mainly involves developing the state equation and augmenting the measurement equation. The optimal filtering outputs of coarse scales are determined. The simulation results show that the noise compression ratio at each scale obtained by our approach is much higher.",

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N2 - A class of dynamic multiscale system (DMS) is dealt with. This paper aims to achieve a better optimal estimation for this class of DMS. A model and an algorithm for this class of DMS is presented. The Haar wavelet approach is described; the description mainly involves developing the state equation and augmenting the measurement equation. The optimal filtering outputs of coarse scales are determined. The simulation results show that the noise compression ratio at each scale obtained by our approach is much higher.

AB - A class of dynamic multiscale system (DMS) is dealt with. This paper aims to achieve a better optimal estimation for this class of DMS. A model and an algorithm for this class of DMS is presented. The Haar wavelet approach is described; the description mainly involves developing the state equation and augmenting the measurement equation. The optimal filtering outputs of coarse scales are determined. The simulation results show that the noise compression ratio at each scale obtained by our approach is much higher.

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On applying Haar wavelet to achieving better optimal estimation for a class of dynamic multiscale system

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