Chandrasekhar-Type Recursive Wiener Filter Using Covariance Information in Linear Discrete-Time Wide-Sense Stationary Stochastic Systems
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概要
- 論文の詳細を見る
This paper designs a Chandrasekhar-type recursive Wiener filter for the white observation noise in linear discrete-time wide-sense stationary stochastic systems. The system matrix in the state-space model of the signal, the crossvariance function of the state variable of the signal with the observed value, the observation matrix for the signal, the variance of the white observation noise and the observed value are assumed to be known. In particular, this paper extends the Chandrasekhar-type recursive Wiener filter for a scalar observation equation to the case of a vector observation equation. A characteristic of the Chandrasekhar-type filter is to calculate the filter gain directly by solving the recursive difference equations.
- 鹿児島大学の論文
- 2005-03-25
著者
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Hermoso-carazo Aurora
Departamento De Estad'istica E Investigaci'on Operativa Universidad De Granada
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Hermoso-carazo Aurora
Departamento De Estad'istica E Investigaci'on Operativa Facultades De Ciencias Universidad
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NAKAMORI Seiichi
鹿児島大学教育学部
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Jim'enez-l'opez Jos'e
Departamento De Estad'istica E Investigaci'on Operativa Universidad De Ja'en
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- Chandrasekhar-Type Recursive Wiener Filter Using Covariance Information in Linear Discrete-Time Wide-Sense Stationary Stochastic Systems