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除噪技术及其在汇率数据中的应用研究
引用本文:马军海,王志强,任彪.除噪技术及其在汇率数据中的应用研究[J].系统工程学报,2005,20(6):620-624.
作者姓名:马军海  王志强  任彪
作者单位:1. 天津大学管理学院,天津,300072;天津财经大学,天津,300222
2. 天津大学管理学院,天津,300072
基金项目:国家自然科学基金资助项目(70271071);天津市教委资助课题(20041702).
摘    要:应用复杂系统理论研究了汇率混沌数据延时嵌入相空间重构方法及其伪相图的获取技术.通过嵌入空间矩阵的分解来得到混沌时序的奇异谱曲线,依此获取混沌时序的内在本质特征及判定其噪声的组成比例,将混沌数据的除噪技术用于汇率数据非线性本质特征的提取.计算结果表明:伪相图在极大程度上反映了原复杂系统的内在本质特征.这一研究对于汇率混沌数据的除噪、本质特征获取、非线性混沌模型的确立技术等都有着极其重要的理论和实际意义.

关 键 词:混沌汇率波动数据  奇异谱曲线  伪相图  除噪技术  本质特征提取
文章编号:1000-5781(2005)06-0620-05
收稿时间:2004-03-19
修稿时间:2004-03-192004-07-13

Study on technology of noise reduction and its application in exchange rate data
MA Jun-hai,WANG Zhi-qiang,REN Biao.Study on technology of noise reduction and its application in exchange rate data[J].Journal of Systems Engineering,2005,20(6):620-624.
Authors:MA Jun-hai  WANG Zhi-qiang  REN Biao
Institution:1. Management School, Tianjin University, Tianjin 300072, China; 2. Tianjin University of Finance and Economics, Tianjin 300222, China
Abstract:With the theory of complicated system, this paper studies the method for restructuring the delayed embedded phase space of chaotic data of exchange rate, and the technology of obtaining its pseudo -phase portrait. Through decomposing the embedded space matrix, we can get the strange spectrum curve of chaotic time series, and can get its internal essential characteristics and determine the noise proportion of chaotic time series. Subsequently the method of reducing noise is used to extract nonlinear essential characteristics of exchange rate data. The calculation result indicates that the pseudo-phase portrait to the utmost extent reflects the internal essential characteristics of original complicated system. Therefore the above studies have very important significance to the technology of noise reduction, extracting essential characteristics and establishing the nonlinear chaotic model of exchange rate data.
Keywords:chaotic vibration data of exchange rote  strange spectrum curve  pseudo-phase portrait  technology of noise reduction  essential characteristics extraction
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