Identification of Partially Unknown System Matrix From Noisy Observation Data via Pseudomeasurement Approach-Reference-Cited by-同舟云学术

Identification of Partially Unknown System Matrix From Noisy Observation Data via Pseudomeasurement Approach

Published:2011-05-05 Issue:0 Volume:2011 Page:27-32
ISSN:2188-4730
Container-title:Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
language:en
Short-container-title:Stochastic Systems Theory and its Applications (SSS)

Author:

KAMEYAMA KENTARO¹,OHSUMI AKIRA²

Affiliation:

1. Department of Mechanical Engineering, Fukui National College of Technology

2. Professor Emeritus of Kyoto Institute of Technology

Publisher

The Institute of Systems, Control and Information Engineers

Subject

General Medicine

Link

https://www.jstage.jst.go.jp/article/sss/2011/0/2011_27/_pdf

Reference9 articles.

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2. [2] A. Ohsumi, K. Kameyama, and K.-I Yamaguchi: Subspace Identification for Continuous-Time Stochastic Systems via Distribution-based Approach, Automatica, vol. 38, no. 2, pp. 63-79, 2002.

3. [3] A. Ohsumi: An Outlook on the Use of Pseudomeasurement in System Identification, Proc. 37th SICE Symp. on Control Theory, Kirishima, pp.91–96, Sep. 2008.

4. [4] A. Ohsumi, T. Kimura, and M. Kono: Kalman Filter-based Identification of Unknown Exogenous Input of Stochastic Linear Systems via Pseudomeasurement Approach, Int. J. of Innovative Computing, Information and Control, vol. 5, no. 1, pp.1–17, 2009.

5. [5] A. Ohsumi, T. Kimura, and M. Kono: A Novel Approach to the Identification of Exogenous Input of Stochastic Systems Using Pseudomeasurement, Proc. of IFAC Symp. SYSID 2009, Saint-Malo, France, pp. 296–301, July, 2009.

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