基于小波的时间序列分析:从工程到金融的出口

Proceedings of the 2000 IEEE Engineering Management Society. EMS - 2000 (Cat. No.00CH37139) Pub Date : 2000-08-13 DOI:10.1109/EMS.2000.872489

J. Norsworthy, D. Li, R. Gorener

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引用次数: 35

摘要

小波分析是应用数学领域近十年来的新发展。小波分析已应用于许多场合，并取得了良好的效果。小波分析主要在信号处理、图像分析和数据压缩三个领域有显著的影响。小波还具有特殊的统计特性，可用于自适应滤波和平滑。许多研究人员正在将其应用扩展到其他领域，如金融工程。本文简要介绍了小波变换方法及其应用。他们的实证研究是在SPLUS (Bruce and Gao, 1996)小波模块平台上进行的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Wavelet-based analysis of time series: an export from engineering to finance

Wavelet analysis is a new development in applied mathematics about ten years in duration. Wavelet analysis has been applied to many situations with favorable results. Wavelet analysis has remarkable impact mainly on three fields, signal processing, image analysis and data compression. Wavelets also have special statistic properties, which can be used in adaptive filtering and smoothing. Many researchers are expanding its application on other fields, such as financial engineering. This author presents a brief review of wavelet methods and its applications. Their empirical study is developed on the SPLUS (Bruce and Gao, 1996) wavelet module platform.

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Proceedings of the 2000 IEEE Engineering Management Society. EMS - 2000 (Cat. No.00CH37139)

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