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Proceedings Paper

Inference on time series based on change points
Author(s): Hong Wang; Jun Zhang; Hongrui Zhao
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Paper Abstract

Change point problem is studied in this paper and a statistical inference method is also proposed which can be used to infer whether change points exist, how many change point there are, which kind they are and where they are. A fact is that change point theory is aimed to solve some problems of nonlinear data processing by statistics. This paper establishes a new algorithm based on Artificial Neural Network (ANN) which has self-organizing feature map (SOM) compared with the conventional approach to analyze change point and change degree. Change point can be applied to segment the phases of time series.

Paper Details

Date Published: 14 November 2007
PDF: 8 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67904C (14 November 2007); doi: 10.1117/12.774821
Show Author Affiliations
Hong Wang, China Univ. of Geosciences (China)
Jun Zhang, Huazhong Agricultural Univ. (China)
Hongrui Zhao, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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