Weighted average extended FIR filter bank to manage the horizon size in nonlinear FIR filtering

Jung Min Pak; Seong Yong Yoo; Myo Taeg Lim; Moon Kyou Song

doi:10.1007/s12555-014-0257-3

Weighted average extended FIR filter bank to manage the horizon size in nonlinear FIR filtering

Jung Min Pak, Seong Yong Yoo, Myo Taeg Lim, Moon Kyou Song

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

In this paper, we propose a novel approach to manage the horizon size in nonlinear finite impulse response (FIR) filtering. The proposed approach is to perform state estimation through a bank of FIR filters called a weighted average extended FIR filter bank (WAEFFB). In the WAEFFB, the state estimate is obtained by weighting the average of multiple estimates from a bank of extended FIR filters that uses different horizon sizes. The horizon sizes used for the WAEFFB are adjusted constantly by maximizing the likelihood function. We show through simulations that the WAEFFB yields better results than the conventional approach that uses a constant (i.e., fixed) horizon size.

Original language	English
Pages (from-to)	138-145
Number of pages	8
Journal	International Journal of Control, Automation and Systems
Volume	13
Issue number	1
DOIs	https://doi.org/10.1007/s12555-014-0257-3
Publication status	Published - 2014 Feb

Bibliographical note

Publisher Copyright:
© 2015, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg.

Keywords

Finite impulse response (FIR) filter
nonlinear system
state estimation
weighted average extended FIR filter bank (WAEFFB)

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications

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10.1007/s12555-014-0257-3

Cite this

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abstract = "In this paper, we propose a novel approach to manage the horizon size in nonlinear finite impulse response (FIR) filtering. The proposed approach is to perform state estimation through a bank of FIR filters called a weighted average extended FIR filter bank (WAEFFB). In the WAEFFB, the state estimate is obtained by weighting the average of multiple estimates from a bank of extended FIR filters that uses different horizon sizes. The horizon sizes used for the WAEFFB are adjusted constantly by maximizing the likelihood function. We show through simulations that the WAEFFB yields better results than the conventional approach that uses a constant (i.e., fixed) horizon size.",

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Y1 - 2014/2

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AB - In this paper, we propose a novel approach to manage the horizon size in nonlinear finite impulse response (FIR) filtering. The proposed approach is to perform state estimation through a bank of FIR filters called a weighted average extended FIR filter bank (WAEFFB). In the WAEFFB, the state estimate is obtained by weighting the average of multiple estimates from a bank of extended FIR filters that uses different horizon sizes. The horizon sizes used for the WAEFFB are adjusted constantly by maximizing the likelihood function. We show through simulations that the WAEFFB yields better results than the conventional approach that uses a constant (i.e., fixed) horizon size.

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KW - state estimation

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Weighted average extended FIR filter bank to manage the horizon size in nonlinear FIR filtering

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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