Design of Recursive Least-Squares Fixed-Lag Smoother using Covariance Information in Linear Continuous Stochastic Systems
スポンサーリンク
概要
- 論文の詳細を見る
This paper newly designs the recursive least-squares (RLS) fixed-lag smoother and filter using the covariance information in linear continuous-time stochastic systems. It is assumed that the signal is observed with additive white observation noise and is uncorrelated with the signal. The estimators require the covariance information of the signal and the variance of the observation noise. The auto-covariance function of the signal is expressed in semi-degenerate kernel form.
- 鹿児島大学の論文
- 2006-02-28
著者
関連論文
- Design of estimators using covariance information with uncertain observations in linear discrete-time distributed parameter systems
- Design of Recursive Least-Squares Fixed-Lag Smoother using Covariance Information in Linear Continuous Stochastic Systems
- Design of Recursive Wiener Fixed-Point Smoother based on Innovations Approach in Linear Discrete-Time Stochastic Systems
- Estimation Technique Using Covariance Information with Relation to Wavelet Transformation in Linear Discrete Stochastic Systems