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50th International Scientific Conference on Electrical, Computer, Electronics and Engineering Vennue: Hotel Grand Flora Dubai, UAE Al- Rigga Road Deira , Near Al-Rigga Metro station , Deira Dubai UAE Date: 20-Dec-2018 More Details
5th International Academic Conference on Computer Sciences and Technological Advancement Vennue: Hotel Istana Kuala Lumpur City Centre 73 Jalan Raja Chulan, Kuala Lumpur, 50200, Malaysia Date: 29-Dec-2018 More Details
This paper newly designs the RLS (recursive least-squares) fixed-lag smoother and filter, based on the innovation theory, in linear continuous-time stochastic systems. It is assumed that the signal is observed with additive white noise and the signal is uncorrelated with the observation noise. It is a characteristic that the estimators use the covariance information of the signal, in the form of the semi-degenerate kernel, and the observation noise. With respect to the RLS fixed-lag smoother, the algorithm for the estimation error variance function is developed to guarantee the stability of the fixed-lag smoother. The proposed estimators have the recursive property in calculating the fixed-lag smoothing and filtering estimates. Also, this paper proposes the Chandrasekhar-type RLS Wiener filter in linear wide-sense stationary stochastic system. Unlike the usual filter including the Riccati-type equations, the Chandrasekhar-type filter does not contain the Riccati-type differential equations and has an advantage of eliminating the possibility of the covariance matrix becoming nonnegative.
Linear continuous systems, Fixed-lag smoother, RLS estimation problem, Covariance information, Wiener-Hopf integral equation, Stochastic signal.
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