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  2007, Vol. 20 Issue (2): 154-161    DOI:
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Study on Symbolization Analysis of Time Series
XIANG Kui, JIANG JingPing
College of Electrical Engineering, Zhejiang University, Hangzhou 310027

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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 wordsSymbolization      Finite Statistic Complexity      Dynamic Transformation     
Received: 26 August 2005     
ZTFLH: N945.16  
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XIANG Kui
JIANG JingPing
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XIANG Kui,JIANG JingPing. Study on Symbolization Analysis of Time Series[J]. , 2007, 20(2): 154-161.
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