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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2009.8
- 수록면
- 4,913 - 4,916 (4page)
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초록· 키워드
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This paper studies an estimation problem of a dominant resonance frequency from time-series data. We proposed an estimatio method which incorporates system identification technique into time-series analysis. However, this method has a problem that the estimated resonance frequency is biased. In this paper, a new method which uses subspace method is proposed based on time-series data. The key idea of this method is to use an auto-covariance function of the time-series data instead of impulse response or ordinary input-output data. Hankel matrix of the time-series is consturcted by the auto-convariance function. Then, subspace method is applied to the Hankel matrix, and the resonance frequency can be calculated. Effectiveness of the method is examined through numerical examples.
목차
Abstract
1. INTRODUCTION
2. PROBLEM FORMULATION
3. TIME-SERIES ANALYSIS USING SYSTEM IDENTIFICATION
4. SUBSPACE METHOD USING AUTO-COVARIANCE
5. NUMERICAL SIMULATION
6. CONCLUSION
REFERENCES
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