Systems Science and Applied Mathematics
Articles Information
Systems Science and Applied Mathematics, Vol.1, No.3, Dec. 2016, Pub. Date: Jan. 9, 2017
Design of FIR Smoother Using Covariance Information for Estimating Signal at Start Time in Linear Continuous Systems
Pages: 29-37 Views: 504 Downloads: 198
Authors
[01] Seiichi Nakamori, Department of Technology, Faculty of Education, Kagoshima University, Kagoshima, Japan.
Abstract
This paper, as a first attempt, examines to design the recursive least-squares (RLS) finite impulse response (FIR) smoother, which estimates the signal at each start time of the finite-time interval in linear continuous-time stochastic systems. It is assumed that the signal is observed with additive white noise and is uncorrelated with the observation noise. It is a characteristic that the FIR smoother uses the covariance information of the signal process in the form of the semi-degenerate kernel and the variance of the observation noise besides the observed value. This paper also presents the recursive algorithm for the estimation error variance function of the RLS-FIR smoother to show the stability condition of the smoother.
Keywords
FIR Smoother, Linear Continuous-Time Stochastic Systems, Wiener-Hopf Integral Equation, White Observation Noise, Convolution Integral
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