Title :
Resonance frequency estimation of time-series data by subspace method
Author :
Hirao, Tomoko ; Adachi, Shuichi
Author_Institution :
Dept. of Appl. Phys. & Physico-Inf., Keio Univ., Yokohama, Japan
Abstract :
This paper studies an estimation problem of a dominant resonance frequency from time-series data. We proposed an estimation 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 constructed by the auto-covariance 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.
Keywords :
Hankel matrices; covariance matrices; data handling; estimation theory; time series; Hankel matrix; auto-covariance function; impulse response; resonance frequency estimation; subspace method; system identification technique; time series data; time-series analysis; Frequency estimation; Resonance; Subspace method; resonance frequency; singular value decomposition; time-series data;
Conference_Titel :
ICCAS-SICE, 2009
Conference_Location :
Fukuoka
Print_ISBN :
978-4-907764-34-0
Electronic_ISBN :
978-4-907764-33-3