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Wavelets pp 205-220 | Cite as

Beyond Wavelets

  • Robert X. Gao
  • Ruqiang Yan
Chapter

Abstract

In previous chapters, we have introduced the theoretical foundation and practical applications related to the wavelet transform. The ability of wavelet transform in adaptive time-scale representation and decomposition of a signal into different subfrequency band presents an efficient signal analysis method without introducing calculation burden (Sweldens 1998). Consequently, it has become a prevailing tool for nonstationary signal processing (e.g., transient pattern identification and location). Given, however, the great variety of signals that appear in real-world applications, there remains plenty of room for continued advancement in the theory of the classical wavelet transform. For example, one of the limitations of the wavelet transform is to modify the base wavelet function to better analyze signals of finite length or duration, instead of infinite or periodic signals (Sweldens 1997).

Keywords

Window Function Lift Scheme Base Wavelet Function Generation Wavelet Forward Procedure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringUniversity of ConnecticutStorrsUSA
  2. 2.School of Instrument Science and EngineeringSoutheast UniversityNanjingChina, People’s Republic

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