时间序列的符号化方法研究

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Abstract Symbolization is an important method for time series analysis, but choosing appropriate symbolization strategy is very difficult. Finite statistic complexity (FSC) can calculate the information quantity contained in the symbol time series, so it is evaluation criterion of symbolizing process. In this paper, several symbolization methods are analyzed including static transformation method, dynamic method, wavelet space method, etc. Eight time series are transformed into the symbol series by different methods and the FSC of all the symbol series are compared from several aspects. These time series which come from different domains are nonlinear and nonstationary. Some meaningful empirical conclusions are thus drawn. All of the analyses imply that the dynamic transformation is the best, and then the integrated one and wavelet space one. Unexpectedly, the static transformation is the most commonly used but the worst.

Key words： Symbolization Finite Statistic Complexity Dynamic Transformation

Received: 26 August 2005

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N945.16

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	XIANG Kui
	JIANG JingPing

Cite this article:

XIANG Kui,JIANG JingPing. Study on Symbolization Analysis of Time Series[J]. , 2007, 20(2): 154-161.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2007/V20/I2/154

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