Abstract：In terms of the basic principle of edge operator in digital image field, a time series pattern representation based on interpolated edge operator(IEO representation) is put forward.This method, according to a measurement standard, chooses the edge point (end point) of each subpattern of time series pattern representation. The measurement standard is the combination of two submeasurement of interpolated edge operator: edge intensity and interpolation error. The IEO representation of time series can not only compress data, but also effectively restrain the influence of noise. Therefore its adaptability is relatively strong, and it can adapt different data feature environment.
[1] Xiao Hui. The Similarity Search and Outlier Detection of Time Series. Ph.D Dissertation. Shanghai, China:Fudan University. Department of Computing and Information Technology, 2005 (in Chinese) (肖 辉.时间序列的相似性查询与异常检测.博士学位论文.上海:复旦大学.计算机与信息技术系, 2005) [2] Keogh E. Fast Similarity Search in the Presence of Longitudinal Scaling in Time Series Databases // Proc of the 9th IEEE International Conference on Tools with Artificial Intelligence. Newport Beach, USA, 1997: 578584 [3] Box G E P, Jenkins G M, Reinsel G C. Time Series Analysis: Forecasting and Control. 3rd Edition.Cambridge, UK: Cambridge University Press, 2005 [4] Li Junkui, Wang Yuanzhen, Liu Chengcheng, et al. Progress and Comparative Study of Time Series Representations: In the Context of Time Series Mining and Modeling [EB/OL]. [20061020]. http://www.paper.edu.cn/downloadpaper.php? serial_number=20610260&type=1 (in Chinese) (李俊奎,王元珍,刘城成,等.时间序列表示进展及比较研究:时间序列挖掘建模环境[EB/OL].[20061020]. http://www.paper.edu.cn/downloadpaper.php? serial_number=20610260&type=1) [5] Sun Jixiang.Image Analysis.Beijing, China: Science Press, 2005: 1690 (in Chinese) (孙即祥.图像分析.北京:科学出版社, 2005: 1690) [6] Luo Hao,Lu Zheming.A Fast Edge Detection Algorithm for Noisy Images. Journal of Test and Measurement Technology, 2004, 18(Z1): 4952 (in Chinese) (罗 浩,陆哲明.一种抗噪快速边缘检测算法.测试技术学报,2004, 18(Z1): 4952) [7] Keogh E, Folias T. The UCR Time Series Data Mining Archive [EB/OL]. [20020731]. http://www.cs.ucr.edu/~eamonn/TSDMA/index.html [8] Prat K B, Fink E. Search for Patterns in Compressed Time Series. International Journal of Image and Graphics, 2002, 2(1): 89106 [9] Keogh E J, Chakrabarti K, Pazzani M J, et al. Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases. Journal of Knowledge and Information Systems, 2001, 3(3): 263286 [10] Yi B K, Faloustsos C. Fast Time Sequence Indexing for Arbitrary Lp Norms // Proc of the 26th International Conference on Very Large Data Bases. Cairo, Egypt, 2000: 385394 [11] Xiao Hui, Feng Xiaofei, Hu Yunfu. A New Segmented Time Warping Distance for Data Mining in Time Series Database // Proc of the International Conference on Machine Learning and Cybernetics. Shanghai, China, 2004, Ⅱ: 12771281
2007, Vol. 20 
