期刊文献+

基于插值边缘算子的时间序列模式表示 被引量:9

Time Series Pattern Representation Based on Interpolated Edge Operator
原文传递
导出
摘要 借鉴数字图像领域中边缘算子的基本思想,提出一种基于插值边缘算子的时间序列分段线性表示方法(简称为 IEO 表示).该方法根据插值边缘算子中的两个子度量:边缘强度和插值误差相结合的度量标准来选取时间序列模式表示中每个子模式的边缘点(端点).时间序列的 IEO 表示不但可以压缩数据,还可以有效抑制噪声的影响,因而具有较强的适应性,可以适应不同的数据特征环境. 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 sub-pattern of.time series pattern representation. The measurement standard is the combination of two sub-measurement 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.
出处 《模式识别与人工智能》 EI CSCD 北大核心 2007年第3期421-427,共7页 Pattern Recognition and Artificial Intelligence
基金 福建省自然科学基金(No.S0650013)
关键词 边缘强度 插值误差 时间序列 分段线性表示 压缩率 拟合误差 Edge Intensity, Interpolation Error, Time Series, Piecewise Linear Representation(PLR), Compression Ratio, Fitting Error
  • 相关文献

参考文献9

  • 1Keogh 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, 1997:578-584
  • 2Box G E P, Jenkins G M, Reinsel G C. Time Series Analysis: Forecasting and Control. 3rd Edition. Cambridge, UK: Cambridge University Press, 2005
  • 3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].[2006-10-20].http://www.paper.edu.cn/downloadpaper.php?serial_number=20610260&type=1)
  • 4罗浩,陆哲明.一种抗噪快速边缘检测算法[J].测试技术学报,2004,18(z1):49-52. 被引量:2
  • 5Keogh E, Folias T. The UCR Time Series Data Mining Archive[EB/OL]. [2002-07-31]. http://www.cs.ucr.edu/~eamonn/TSDMA/index. html
  • 6Prat K B, Fink E. Search for Patterns in Compressed Time Series. International Journal of Image and Graphics, 2002, 2(1):89-106
  • 7Keogh 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):263-286
  • 8Yi 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, 2000:385-394
  • 9Xiao 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: 1277-1281

二级参考文献1

共引文献2

同被引文献101

引证文献9

二级引证文献63

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部