Estimation Algorithm from Delayed Measurements with Correlation between Signal and Noise Using Covariance Information(Systems and Control)
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概要
- 論文の詳細を見る
This paper considers the least-squares linear estimation problem of signals from randomly delayed observations when the additive white noise is correlated with the signal. The delay values are treated as unknown variables, modelled by a binary white noise with values zero or one; these values indicate that the measurements arrive in time or they are delayed by one sampling time. A recursive one-stage prediction and filtering algorithm is obtained by an innovation approach and do not use the state-space model of the signal. It is assumed that both, the autocovariance functions of the signal and the crosscovariance function between the signal and the observation noise are expressed in a semi-degenerate kernel form; using this information and the delay probabilities, the estimators are recursively obtained.
- 社団法人電子情報通信学会の論文
- 2004-05-01
著者
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Linares-perez Josefa
The Department Of Statistics Granada University
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Linares-perez Josefa
Department Of Statistics Granada University
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NAKAMORI Seiichi
Faculty of Education, Kagoshima University
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CABALLERO-AGUILA Raquel
Department of Statistics, Jaen University
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HERMOSO-CARAZOf Aurora
Department of Statistics, Granada University
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Nakamori Seiichi
Faculty Of Education Kagoshima University
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Hermoso-carazo Aurora
Department Of Statistics Granada University
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Caballero-aguila Raquel
Department Of Statistics Jaen University
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Nakamori S
The Faculty Of Education Kagoshima University
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