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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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Norsworthy et al. (2002) studied this question.
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