On the Approximation of Optimal Realizable Linear Filters Using a Karhunen-Loève Expansion

T. E. Fortmann, B. D.O. Anderson

Research output: Contribution to journalLetterpeer-review

14 Citations (Scopus)

Abstract

The Karhunen-Loève expansion of a random process is used to derive the impulse response of the optimal realizable linear estimator for the process. The expansion is truncated to yield an approximate state-variable model of the process in terms of the first N eigenvalues and eigenfunctions. The Kalmaa-Bucy filter for this model provides an approximate realizable linear estimator which approaches the optimal one as N → ∞. A bound on the truncation error is obtained.

Original languageEnglish
Pages (from-to)561-564
Number of pages4
JournalIEEE Transactions on Information Theory
Volume19
Issue number4
DOIs
Publication statusPublished - Jul 1973
Externally publishedYes

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