NDLI: An H/sub /spl infin// optimization and its fast algorithm for time-variant system identification

Content Provider	IEEE Xplore Digital Library
Author	Nishiyama, K.
Copyright Year	1991
Abstract	In some estimation or identification techniques, a forgetting factor /spl rho/ has been used to improve the tracking performance for time-varying systems. However, the value of /spl rho/ has been typically determined empirically, without any evidence of optimality. In our previous work, this open problem is solved using the framework of H/sub /spl infin// optimization. The resultant H/sub /spl infin// filter enables the forgetting factor /spl rho/ to be optimized through a process noise that is determined by the filter Riccati equation. This paper seeks to further explain the previously derived H/sub /spl infin// filter, giving an H/sub /spl infin// interpretation of its tracking capability. Additionally, a fast algorithm of the H/sub /spl infin// filter, called the fast H/sub /spl infin// filter, is presented when the observation matrix has a shifting property. Finally, the effectiveness of the derived fast algorithm is illustrated for time-variant system identification using several computer simulations. Here, the fast H/sub /spl infin// filter is shown to outperform the well known least-mean-square algorithm and the fast Kalman filter in convergence rate.
Sponsorship	IEEE Signal Processing Society
Starting Page	1335
Ending Page	1342
Page Count	8
File Size	392333
File Format	PDF
ISSN	1053587X
Volume Number	52
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-05-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	System identification Signal processing algorithms Adaptive filters Filtering algorithms Riccati equations Convergence Least squares approximation Parameter estimation Time varying systems Computer simulation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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