Applying the Prediction Method based upon the Scale Expansion to the Feature Extraction of Fractal Geometry

Bibliographic Information

Other Title
  • スケール伸長変換を用いたフラクタル図形の特徴づけとその応用

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Description

It is known that the natural phenomina and the data representing social activities have the self-similarity, and are explained by using the fractal theroy. But usually, real observed data include a kind of white noise and specific pattern which are superposed on the ideal fractal geometry. Evenmore, the parameters of the fractal geometry such as the fractal dimension vary along the time. Therefore, it is necessary for the design of database management system of the fractal geometry to develop a efficient method to detect such kind of features and to divide to several segments of fractal geometry where the parameters are constant. This report deals with the characterization of fractal geometry(noise reduction, extarction of feature patterns and segmentation)by using the prediction of fractal geometry based upon the scale expansion given by the authors. The scale expansion corresponds to a kind of nonlinear fltering to detect the feature patterns from the fractal geometry. As an application, the the feature extraction for stock trend and the communication traffic are shown for the cases of fractral time series. And we also show the extraction of the feature patterns of cloud.

Journal

  • Technical report of IEICE. DSP

    Technical report of IEICE. DSP 98 (3), 91-98, 1998-04-17

    The Institute of Electronics, Information and Communication Engineers

Keywords

Details 詳細情報について

  • CRID
    1572261552345707648
  • NII Article ID
    110003279848
  • NII Book ID
    AN10060786
  • ISSN
    09135685
  • Text Lang
    ja
  • Data Source
    • CiNii Articles

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