지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2012.1
- 수록면
- 106 - 112 (7page)
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초록· 키워드
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Real-life time series characteristic data has significant amount of non-stationary components, especially periodic components in nature. Extracting such components has required many ad-hoc techniques with external parameters set by users in case-by-case manner. In our study, we evaluate whether Hilbert-Huang Transform, a new tool of time-series analysis can be used for effective analysis of such data. It is divided into two points : 1) how effective it is in finding periodic components, 2) whether we can use its results directly in detecting values outside control limits, for which a traditional method such as ARIMA had been used.
We use glass furnace temperature data to illustrate the method.
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참고문헌 (15)
참고문헌 신청
Box, George E. P. / 1994 / Time Series Analysis Forecasting and Control / Prentice Hall
Brigham, E. O / 2002 / The Fast Fourier Transform / Prentice-Hall
Chui, Charles K / 1992 / An Introduction to Wavelets / Academic Press
Flandrin, P. / 2003 / Empirical mode decomposition as a filterbank / IEEE Signal Proc Lett 11 : 112 ~ 114
Hogan, Jeffrey A. / 2004 / Time-Frequency and Time-Scale Methods : Adaptive Decompositions, Uncertainty Principles, and Sampling / Springer Verlag
Brigham, E. O / 2002 / The Fast Fourier Transform / Prentice-Hall
Chui, Charles K / 1992 / An Introduction to Wavelets / Academic Press
Flandrin, P. / 2003 / Empirical mode decomposition as a filterbank / IEEE Signal Proc Lett 11 : 112 ~ 114
Hogan, Jeffrey A. / 2004 / Time-Frequency and Time-Scale Methods : Adaptive Decompositions, Uncertainty Principles, and Sampling / Springer Verlag
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