| 書目名稱 | Essential Wavelets for Statistical Applications and Data Analysis | | 編輯 | R. Todd Ogden | | 視頻video | http://file.papertrans.cn/316/315568/315568.mp4 | | 概述 | Includes supplementary material: | | 圖書封面 |  | | 描述 | I once heard the book by Meyer (1993) described as a "vulgarization" of wavelets. While this is true in one sense of the word, that of making a sub- ject popular (Meyer‘s book is one of the early works written with the non- specialist in mind), the implication seems to be that such an attempt some- how cheapens or coarsens the subject. I have to disagree that popularity goes hand-in-hand with debasement. is certainly a beautiful theory underlying wavelet analysis, there is While there plenty of beauty left over for the applications of wavelet methods. This book is also written for the non-specialist, and therefore its main thrust is toward wavelet applications. Enough theory is given to help the reader gain a basic understanding of how wavelets work in practice, but much of the theory can be presented using only a basic level of mathematics. Only one theorem is for- mally stated in this book, with only one proof. And these are only included to introduce some key concepts in a natural way. | | 出版日期 | Book 1997 | | 關(guān)鍵詞 | Estimator; Invariant; Regression; Signal; Wavelet; algorithm; calculus; data analysis; discrete Fourier tran | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4612-0709-2 | | isbn_softcover | 978-1-4612-6876-5 | | isbn_ebook | 978-1-4612-0709-2 | | copyright | Springer Science+Business Media New York 1997 |
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