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Wavelet-Based Signal Processing and Applications * C .

Sidney Burrus, Haitao Guo

Journal of the Indian Institute of Science(2018)

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Abstract
This chapter gives a brief discussion of several areas of application. It is intended to show what areas and what tools are being developed and to give some references to books, articles, and conference papers where the topics can be further pursued. In other words, it is a sort of annotated bibliography that does not pretend to be complete. Indeed, it is impossible to be complete or up-to-date in such a rapidly developing new area and in an introductory book. In this chapter, we brie y consider the application of wavelet systems from two perspectives. First, we look at wavelets as a tool for denoising and compressing a wide variety of signals. Second, we very brie y list several problems where the application of these tools shows promise or has already achieved signi cant success. References will be given to guide the reader to the details of these applications, which are beyond the scope of this book.
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Key words
Wavelet Transform,Deep Learning,Hyperspectral Imaging,Backpropagation Learning,Feedforward Neural Networks
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