Extended Levinson and Chandrasekhar Equations for General Discrete-Time Linear Estimation Problems
1978 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 23, no 4, 653-659 p.Article in journal (Refereed) Published
Recursive algorithrms for the solution of linear least-squares estimation problems have been based mainly on state-space models. It has been known, however, that recursive Levinson-Whittle-Wiggins-Robinson (LWR) algorithms exist for stationary time-series, using only input-output information (i.e, covariance matrices). By introducing a way of classifying stochastic processes in terms of an "index of nonstationarity" we derive extended LWR algorithms for nonstationary processes We show also how adding state-space structure to the covariance matrix allows us to specialize these general results to state-space type estimation algorithms. In particular, the Chandrasekhar equations are shown to be natural descendants of the extended LWR algorithm.
Place, publisher, year, edition, pages
IEEE Control Systems Society , 1978. Vol. 23, no 4, 653-659 p.
Chandrasekhar equations, Covariance matrices, Least-squares estimation, Linear systems, Recursive estimation
IdentifiersURN: urn:nbn:se:liu:diva-100998DOI: 10.1109/TAC.1978.1101797OAI: oai:DiVA.org:liu-100998DiVA: diva2:664719