Measure observability by the generalized informational correlation

Chen Badong; Hu Jinchun; Li Hongbo; Sun Zengqi

doi:10.1109/CDC.2007.4434179

Measure observability by the generalized informational correlation

Chen Badong
, Hu Jinchun
, Li Hongbo
, Sun Zengqi

Tsinghua University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

Informational correlation coefficient (ICC) can be used to measure the degree of observability for a system. In this paper, we define the generalized informational correlation coefficient (GICC), which is suitable for both discrete and continuous random variables. For the case in which the probability density functions (PDFs) are regularly supersummable, we obtain the exact value of GICC. Moreover, for the linear, stochastically autonomous system, we derive the explicit formula for the degree of observability, and prove the equivalence between the proposed measure and the traditional rank condition. Finally, a simple example is given to compare the discrete state case and the continuous state case.

Original language	English
Title of host publication	Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5570-5574
Number of pages	5
ISBN (Print)	1424414989, 9781424414987
DOIs	https://doi.org/10.1109/CDC.2007.4434179
State	Published - 2007
Externally published	Yes
Event	46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA, United States Duration: 12 Dec 2007 → 14 Dec 2007

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	46th IEEE Conference on Decision and Control 2007, CDC
Country/Territory	United States
City	New Orleans, LA
Period	12/12/07 → 14/12/07

Access to Document

10.1109/CDC.2007.4434179

Cite this

Badong, C., Jinchun, H., Hongbo, L., & Zengqi, S. (2007). Measure observability by the generalized informational correlation. In Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC (pp. 5570-5574). Article 4434179 (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2007.4434179

@inproceedings{04275b838184423faa4dacd38774c91e,

title = "Measure observability by the generalized informational correlation",

abstract = "Informational correlation coefficient (ICC) can be used to measure the degree of observability for a system. In this paper, we define the generalized informational correlation coefficient (GICC), which is suitable for both discrete and continuous random variables. For the case in which the probability density functions (PDFs) are regularly supersummable, we obtain the exact value of GICC. Moreover, for the linear, stochastically autonomous system, we derive the explicit formula for the degree of observability, and prove the equivalence between the proposed measure and the traditional rank condition. Finally, a simple example is given to compare the discrete state case and the continuous state case.",

author = "Chen Badong and Hu Jinchun and Li Hongbo and Sun Zengqi",

year = "2007",

doi = "10.1109/CDC.2007.4434179",

language = "英语",

isbn = "1424414989",

series = "Proceedings of the IEEE Conference on Decision and Control",

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

pages = "5570--5574",

booktitle = "Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC",

note = "46th IEEE Conference on Decision and Control 2007, CDC ; Conference date: 12-12-2007 Through 14-12-2007",

}

Badong, C, Jinchun, H, Hongbo, L & Zengqi, S 2007, Measure observability by the generalized informational correlation. in Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC., 4434179, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 5570-5574, 46th IEEE Conference on Decision and Control 2007, CDC, New Orleans, LA, United States, 12/12/07. https://doi.org/10.1109/CDC.2007.4434179

Measure observability by the generalized informational correlation. / Badong, Chen; Jinchun, Hu; Hongbo, Li et al.
Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC. Institute of Electrical and Electronics Engineers Inc., 2007. p. 5570-5574 4434179 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Jinchun, Hu

AU - Hongbo, Li

AU - Zengqi, Sun

PY - 2007

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N2 - Informational correlation coefficient (ICC) can be used to measure the degree of observability for a system. In this paper, we define the generalized informational correlation coefficient (GICC), which is suitable for both discrete and continuous random variables. For the case in which the probability density functions (PDFs) are regularly supersummable, we obtain the exact value of GICC. Moreover, for the linear, stochastically autonomous system, we derive the explicit formula for the degree of observability, and prove the equivalence between the proposed measure and the traditional rank condition. Finally, a simple example is given to compare the discrete state case and the continuous state case.

AB - Informational correlation coefficient (ICC) can be used to measure the degree of observability for a system. In this paper, we define the generalized informational correlation coefficient (GICC), which is suitable for both discrete and continuous random variables. For the case in which the probability density functions (PDFs) are regularly supersummable, we obtain the exact value of GICC. Moreover, for the linear, stochastically autonomous system, we derive the explicit formula for the degree of observability, and prove the equivalence between the proposed measure and the traditional rank condition. Finally, a simple example is given to compare the discrete state case and the continuous state case.

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M3 - 会议稿件

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BT - Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 46th IEEE Conference on Decision and Control 2007, CDC

Y2 - 12 December 2007 through 14 December 2007

ER -

Measure observability by the generalized informational correlation

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