New multi-step fir predictors for state-space signal models

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Abstract

In this letter, we propose a new multi-step maximum likelihood predictor with a finite impulse response (FIR) structure for discretetime state-space signal models. This predictor is called a maximum likelihood FIR predictor (MLFP). The MLFP is linear with the most recent finite outputs and does not require a prior initial state information on a receding horizon. It is shown that the proposed MLFP possesses the unbiasedness property and the deadbeat property. Simulation study illustrates that the proposed MLFP is more robust against uncertainties and faster in convergence than the conventional multi-step Kalman predictor.

Original languageEnglish
Pages (from-to)1233-1236
Number of pages4
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE92-A
Issue number4
DOIs
Publication statusPublished - 2009
Externally publishedYes

Keywords

  • Deadbeat property
  • FIR structure
  • Maximum likelihood
  • Multi-step predictor
  • Unbiasedness property

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics

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