Автор: Cajetan M. Akujuobi
Издательство: Springer
Год: 2022
Страниц: 657
Язык: английский
Формат: pdf (true)
Размер: 18.1 MB
This textbook is unique because of its in-depth treatment of the applications of wavelets and wavelet transforms to many areas, across many disciplines. The book is written to serve the needs of a one or two semester course at either the undergraduate or graduate level. The author uses a very simplified, accessible approach that de-emphasizes mathematical rigor. The presentation includes many diagrams to illustrate points being discussed and uses MATLAB for all of application code. The author reinforces concepts introduced in the book with easy to grasp review questions and problems, tailored to each specific chapter for better mastery of the subject matter. This book enables students to understand the fundamental concepts of wavelets and wavelet transforms, as well as how to use them for problem solutions in digital signal and image processing, mixed-signal testing, space applications, aerospace applications, biomedical, cyber security, homeland security and many other application areas.
We live in the Information Age where information is analyzed, synthetized, and stored at a much faster rate using different techniques such as different wavelets and wavelet transforms. For many decades, wavelets and wavelet transforms have received much attention in the literature of many communities in the areas of science and engineering. There are different types of wavelets. These wavelets are used as analyzing tools by pure mathematicians (in harmonic analysis, for the study of Calderon-Zygmund operators), by statisticians (in nonparametric estimation), and by electrical engineers (in signal analysis).
In physics, wavelets are used because of their applications to time-frequency or phase-space analysis and their renormalization concepts. In computer vision research, wavelets are used for "scale-space" methods. In stochastic processes, they are used in application of self-similar processes. Because of wavelets and wavelet transforms’ connections with multirate filtering, quadrature mirror filters, and sub-band coding, they have found home in the digital signal processing community. The image processing community uses wavelets because of their applications in pyramidal image representation and compression. In harmonic analysis, wavelets are used because of the special properties of wavelet bases, while the speech processing community uses wavelets because of their efficient signal representation, event extraction, and the mimicking of the human auditory system.
Provides textbook coverage of Wavelets and applications, suitable for one and two semester courses, either at the undergraduate or graduate level;
Discusses many types of wavelets and their applications across many disciplines;
Includes MATLAB code illustrations to simplify the understanding of the various applications;
Uses many illustrations, figures, tables, and visual comparisons to simplify and clarify the various concepts of wavelets, wavelet transforms and the various application areas;
Ends each chapter with review questions/answers, as well as exercises to reinforce and test concepts introduced;
Solutions manual and PowerPoint slides for each chapter available for instructors.
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