文件名称:
The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
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文件大小: 2mb
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上传时间: 2009-07-12
详细说明： A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the `empirical mode decomposition' method with which any complicated data set can be decomposed into a nite and often small number of `intrinsic mode functions' that admit well-behaved Hilbert transforms. This decomposition method is adaptive, and, therefore, highly ecient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and non-stationary processes. With the Hilbert transform, the `instrinic mode functions' yield instantaneous frequencies as functions of time that give sharp identi cations of imbedded structures. The nal presentation of the results is an energy{frequency{time distribution, designated as the Hilbert spectrum. In this method, the main conceptual innovations are the introduction of `intrinsic mode functions' based on local properties of the signal, which makes the instantaneous frequency meaningful; and the introduction of the instantaneous frequencies for complicated data sets, which eliminate the need for spurious harmonics to represent nonlinear and non-stationary signals. Examples from the numerical results of the classical nonlinear equation systems and data representing natural phenomena are given to demonstrate the power of this new method. Classical nonlinear system data are especially interesting, for they serve to illustrate the roles played by the nonlinear and non-stationary e ects in the energy{frequency{time distribution. ...展开收缩
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