Least-squares linear estimation of signals from observations with Markovian delays

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:236

Article

Garcia-Ligero, M. J.¹ 

[1] Univ Granada, Dpto Estadist EIO, Fac Ciencias, E-18071 Granada, Spain

关键词: Markovian delays;    Covariance information;    Least-squares estimation;   

DOI  :  10.1016/j.cam.2011.06.021

来源: Elsevier

【 摘 要 】

The least-squares linear estimation of signals from randomly delayed measurements is addressed when the delay is modeled by a homogeneous Markov chain. To estimate the signal, recursive filtering and fixed-point smoothing algorithms are derived, using an innovation approach, assuming that the covariance functions of the processes involved in the observation equation are known. Recursive formulas for filtering and fixed-point smoothing error covariance matrices are obtained to measure the goodness of the proposed estimators. (C) 2011 Elsevier B.V. All rights reserved.

【 授权许可】

Free