Linear algebra, signal processing, and wavelets - a unified approach : python version / by Øyvind Ryan.
2019
QA184.2
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Details
Title
Linear algebra, signal processing, and wavelets - a unified approach : python version / by Øyvind Ryan.
Author
Ryan, Øyvind., author
ISBN
9783030029401 (electronic book)
3030029409 (electronic book)
9783030029395
3030029395
3030029409 (electronic book)
9783030029395
3030029395
Publication Details
Cham : Springer, 2019.
Language
English
Description
1 online resource
Call Number
QA184.2
Dewey Decimal Classification
512/.5
Summary
This book offers a user friendly, hands-on, and systematic introduction to applied and computational harmonic analysis: to Fourier analysis, signal processing and wavelets; and to their interplay and applications. The approach is novel, and the book can be used in undergraduate courses, for example, following a first course in linear algebra, but is also suitable for use in graduate level courses. The book will benefit anyone with a basic background in linear algebra. It defines fundamental concepts in signal processing and wavelet theory, assuming only a familiarity with elementary linear algebra. No background in signal processing is needed. Additionally, the book demonstrates in detail why linear algebra is often the best way to go. Those with only a signal processing background are also introduced to the world of linear algebra, although a full course is recommended. The book comes in two versions: one based on MATLAB, and one on Python, demonstrating the feasibility and applications of both approaches. Most of the code is available interactively. The applications mainly involve sound and images. The book also includes a rich set of exercises, many of which are of a computational nature.
Bibliography, etc. Note
Includes bibliographical references and index.
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Access limited to authorized users.
Series
Springer undergraduate texts in mathematics and technology.
Available in Other Form
Print version: 9783030029395
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Table of Contents
Sound and Fourier series
Digital sound and discrete Fourier analysis
Discrete time filters
Motivation for wavelets and some simple examples
The filter representation of wavelets
Constructing interesting wavelets
The polyphase representation of filter bank transforms
Digital images
Using tensor products to apply wavelets to images
Appendix A: Basic linear algebra.
Digital sound and discrete Fourier analysis
Discrete time filters
Motivation for wavelets and some simple examples
The filter representation of wavelets
Constructing interesting wavelets
The polyphase representation of filter bank transforms
Digital images
Using tensor products to apply wavelets to images
Appendix A: Basic linear algebra.