Kalman filtering of large-scale geophysical flows by approximations based on Markov random field and wavelet

Toshio M. Chin; Arthur J. Mariano

Kalman filtering of large-scale geophysical flows by approximations based on Markov random field and wavelet

Toshio M. Chin, Arthur J. Mariano

Ocean Sciences

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Large-scale extended Kalman filters for atmospheric and oceanic circulation models can readily be approximated using a wavelet transform or a Markov random field model. For a filtering problem where the unknown field of the state variables is highly correlated and the observations are relatively sparse, the wavelet-approximated filter seems more appropriate. For a problem in which the covariance matrix is non-singular and a relatively large quantity of independent observations are processed, the MRF-approximated filter seems more appropriate.

Original language	English (US)
Pages (from-to)	2785-2788
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	5
State	Published - Jan 1 1995
Event	Proceedings of the 1995 20th International Conference on Acoustics, Speech, and Signal Processing. Part 2 (of 5) - Detroit, MI, USA Duration: May 9 1995 → May 12 1995

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Cite this

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title = "Kalman filtering of large-scale geophysical flows by approximations based on Markov random field and wavelet",

abstract = "Large-scale extended Kalman filters for atmospheric and oceanic circulation models can readily be approximated using a wavelet transform or a Markov random field model. For a filtering problem where the unknown field of the state variables is highly correlated and the observations are relatively sparse, the wavelet-approximated filter seems more appropriate. For a problem in which the covariance matrix is non-singular and a relatively large quantity of independent observations are processed, the MRF-approximated filter seems more appropriate.",

author = "Chin, {Toshio M.} and Mariano, {Arthur J.}",

year = "1995",

month = jan,

day = "1",

language = "English (US)",

volume = "5",

pages = "2785--2788",

journal = "Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing",

issn = "0736-7791",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the 1995 20th International Conference on Acoustics, Speech, and Signal Processing. Part 2 (of 5) ; Conference date: 09-05-1995 Through 12-05-1995",

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T1 - Kalman filtering of large-scale geophysical flows by approximations based on Markov random field and wavelet

AU - Chin, Toshio M.

AU - Mariano, Arthur J.

PY - 1995/1/1

Y1 - 1995/1/1

N2 - Large-scale extended Kalman filters for atmospheric and oceanic circulation models can readily be approximated using a wavelet transform or a Markov random field model. For a filtering problem where the unknown field of the state variables is highly correlated and the observations are relatively sparse, the wavelet-approximated filter seems more appropriate. For a problem in which the covariance matrix is non-singular and a relatively large quantity of independent observations are processed, the MRF-approximated filter seems more appropriate.

AB - Large-scale extended Kalman filters for atmospheric and oceanic circulation models can readily be approximated using a wavelet transform or a Markov random field model. For a filtering problem where the unknown field of the state variables is highly correlated and the observations are relatively sparse, the wavelet-approximated filter seems more appropriate. For a problem in which the covariance matrix is non-singular and a relatively large quantity of independent observations are processed, the MRF-approximated filter seems more appropriate.

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M3 - Conference article

AN - SCOPUS:0028996466

VL - 5

SP - 2785

EP - 2788

JO - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

JF - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

SN - 0736-7791

T2 - Proceedings of the 1995 20th International Conference on Acoustics, Speech, and Signal Processing. Part 2 (of 5)

Y2 - 9 May 1995 through 12 May 1995

ER -

Kalman filtering of large-scale geophysical flows by approximations based on Markov random field and wavelet

Abstract

ASJC Scopus subject areas

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