The Application of Multiwavelets to Chaotic Time Series Analysis

被引：0
|
作者：
Zhao, Zhihong [1 ]
Yang, Shaopu [2 ]
Lei, Yu [1 ]
机构：
[1] Shijiazhuang Tiedao Univ, Sch Comp & Informat, Shijiazhuang 050043, Hebei, Peoples R China
[2] Inst Traff Environm & Safety Engn, Shijiazhuang 050043, Hebei, Peoples R China
来源：
PROCEEDINGS OF 2013 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT AUTOMATION & INTELLIGENT TECHNOLOGY AND SYSTEMS | 2013年 / 255卷
基金：
中国国家自然科学基金;
关键词：
Multiwavelets; Chaotic time series; Lorenz time series;
D O I：
10.1007/978-3-642-38460-8_6
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Multiwavelets offer symmetry, orthogonality, and short support, which is not possible with scalar wavelet. In this paper, we analyzed chaotic time series using multiwavelets. Two benchmark chaotic time series and the real-world data of Sunspots time series were analyzed. Three type of accuracy criteria: Mean square error, Root mean square error and Mean absolute error were used to measure the performance of the reconstruction. And the results were compared to the scalar wavelet. Experimental results indicate that multiwavelets were superior to scalar wavelet for chaotic time series analysis.
引用
收藏
页码：51 / 57
页数：7
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