International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 5, No. 9, 8 Aug. 2013
Cover page and Table of Contents: PDF (size: 693KB)
Design of RLS Wiener Smoother and Filter from Randomly Delayed Observations in Linear Discrete-Time Stochastic Systems
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Author(s)
Seiichi Nakamori
1,*
Index Terms
Discrete-Time Stochastic Systems, RLS Wiener Filter, RLS Wiener Fixed-Point Smoother, Randomly Delayed Observations, Covariance Information
Abstract
This paper presents the new algorithm of the recursive least-squares (RLS) Wiener fixed-point smoother and filter based on the randomly delayed observed values by one sampling time in linear discrete-time wide-sense stationary stochastic systems. The observed value y(k) consists of the observed value y¯(k-1) with the probability p(k) and of y¯(k) with the probability 1-p(k). It is assumed that the delayed measurements are characterized by Bernoulli random variables. The observation y¯(k) is given as the sum of the signal z(k)=Hx(k) and the white observation noise v(k). The RLS Wiener estimators use the following information: (a) the system matrix for the state vector x(k); (b) the observation matrix H (c) the variance of the state vector x(k); (d) the delayed probability p(k); (e) the variance of white observation noise v(k); (f) the input noise variance of the state equation for the augmented vector v¯(k) related with the observation noise.
Cite This Paper
Seiichi Nakamori, "Design of RLS Wiener Smoother and Filter from Randomly Delayed Observations in Linear Discrete-Time Stochastic Systems", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.9, pp.1-20, 2013. DOI:10.5815/ijitcs.2013.09.01
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