On the approximation of optimal realizable linear filters using a Karhunen-Loeve expansion (Corresp.)

  • Authors:
  • T. Fortmann;B. Anderson

  • Affiliations:
  • -;-

  • Venue:
  • IEEE Transactions on Information Theory
  • Year:
  • 2006

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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 firstNeigenvalues and eigenfunctions. The Kalman-Bucy filter for this model provides an approximate realizable linear estimator which approaches the optimal one asN rightarrow infty. A bound on the truncation error is obtained.