DISCRETE FOURIER AND WAVELET TRANSFORMS

Goodman Roe W

ISBN 10: 9814725765 / ISBN 13: 9789814725767

Published by World Scientific, 2016

About this Item

DISCRETE FOURIER AND WAVELET TRANSFORMS | Goodman Roe W | Buch | Gebunden | Englisch | 2016 | World Scientific | EAN 9789814725767 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 104161590

Bibliographic Details

• Title: DISCRETE FOURIER AND WAVELET TRANSFORMS
• Publisher: World Scientific
• Publication Date: 2016
• Language: English
• ISBN 10: 9814725765
• ISBN 13: 9789814725767
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 21D millimeters 250 millimeters width by 175 millimeters height by 21 millimeters depth
• Weight: 704 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

"This book is suitable as a textbook for an introductory undergraduate mathematics course on discrete Fourier and wavelet transforms for students with background in calculus and linear algebra. The particular strength of this book is its accessibility to students with no background in analysis. The exercises and computer explorations provide the reader with many opportunities for active learning. Studying from this text will also help students strengthen their background in linear algebra."

Mathematical Association of America

This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.

It explains how to use the Fourier matrix to extract frequency information from a digital signal and how to use circulant matrices to emphasize selected frequency ranges. It introduces discrete wavelet transforms for digital signals through the lifting method and illustrates through examples and computer explorations how these transforms are used in signal and image processing. Then the general theory of discrete wavelet transforms is developed via the matrix algebra of two-channel filter banks. Finally, wavelet transforms for analog signals are constructed based on filter bank results already presented, and the mathematical framework of multiresolution analysis is examined.