Inference on time series based on change points

Hong Wang; Jun Zhang; Hongrui Zhao

doi:10.1117/12.774821

14 November 2007 Inference on time series based on change points

Hong Wang, Jun Zhang, Hongrui Zhao

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67904C (2007) https://doi.org/10.1117/12.774821
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Hong Wang, Jun Zhang, and Hongrui Zhao "Inference on time series based on change points", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67904C (14 November 2007); https://doi.org/10.1117/12.774821

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