Strong consistency and CLT for the random decrement estimator
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- 作者：Pierre Bernard and Liang Zhen Lei
- 关键词：Random decrement estimator ; law of large numbers ; center limit theorem
- 刊名：Acta Mathematica Sinica
- 出版时间：September 2010
- 出版年：2010
- 期刊代码：2_1439-8516
- 类别：mat
- 卷：26
- 期：9
- 页码：1613-1626
- 数据来源：sp
摘要
The random decrement technique (RDT), introduced in the sixties by Cole [NASA CR-2005, 1973], is a very performing method of analysis for vibration signature of a structure under ambient loading. But the real nature of the random decrement signature has been misunderstood until now. Moreover, the various interpretations were made in continuous time setting, while real experimental data are obtained in discrete time. In this paper, the really implemental discrete time algorithms are studied. The asymptotic analysis as the number of triggering points go to infinity is achieved, and a Law of Large Numbers as well as a Central Limit Theorem is proved. Moreover, the limit as the discretization time step goes to zero is computed, giving more tractable formulas to approximate the random decrement. This is a new approach of the famous “Kac-Slepian paradox” [Ann. Math. Stat., 30, 1215–1228 (1959)]. The main point might be that the RDT is a very efficient functional estimator of the correlation function of a stationary ergodic Gaussian process. Very fast, it is to classical estimators what Fast Fourier Transform (FFT) is to ordinary Discrete Fourier Transforms.