Design of Linear Discrete-Time Stochastic Estimators Using Covariance Information in Krein Spaces
スポンサーリンク
概要
- 論文の詳細を見る
This paper proposes new recursive fixed-point smoother and filter using covariance information in linear discrete-time stochastic systems. In this paper, to be able to treat the estimation of the stochastic signal, a performance criterion, extended from the criterion in the H_∞ estimation problem, is newly proposed. The criterion is transformed equivalently into a mm-max principle in game theory, and an observation equation in a Krein space is obtained as a result. The estimation accuracy of the proposed estimators are compared with the recursive least-squares (RLS) Wiener estimators, the Kalman filter and the fixed-point smoother based on the state-space model.
- 社団法人電子情報通信学会の論文
- 2002-04-01
著者
関連論文
- Recursive Estimation Algorithm Based on Covariances for Uncertainly Observed Signals Correlated with Noise
- Filtering in Generalized Signal-Dependent Noise Model Using Covariance Information
- Fixed-Lag Smoothing Algorithm under Non-independent Uncertainty(Digital Signal Processing)
- Fixed-Point, Fixed-Interval and Fixed-Lag Smoothing Algorithms from Uncertain Observations Based on Covariances(Digital Signal Processing)
- Estimation Algorithm from Delayed Measurements with Correlation between Signal and Noise Using Covariance Information(Systems and Control)
- Fixed-Interval Smoothing from Uncertain Observations with White Plus Coloured Noises Using Covariance Information(Digital Signal Processing)
- Second-Order Polynomial Estimators from Non-independent Uncertain Observations Using Covariance Information
- Recursive Estimation Technique of Signal from Output Measurement Data in Linear Discrete-Time Systems
- Estimation Technique Using Covariance Data in Linear Continuous Stochastic Systems
- Optimal Filtering Algorithm Using Covariance Information In Linear Continuous Distributed Parameter Systems
- Design of Linear Discrete-Time Stochastic Estimators Using Covariance Information in Krein Spaces
- Design of Recursive Wiener Smoother Given Covariance Information
- Design of Estimators Using Covarianee Information in Discrete-Time Stochastic Systems with Nonlinear Observation Mechanism