Название: Mathematical Methods and Algorithms for Signal Processing
Автор: Todd K. Moon, Wynn C. Stirling
Издательство: Prentice Hall
Размер: 37.35 Mb
The purpose of this book is to bridge the gap between introductory signal processing classes and the mathematics prevalent in contemporary signal processing research and practice, by providing a unified applied treatment of fundamental mathematics, seasoned with demonstrations using MATLAB®. This book is intended not only for current students of signal processing, but also for practicing engineers who must be able to access the signal processing research literature, and for researchers looking for a particular result to apply. It is thus intended both as a textbook and as a reference.
Both the theory and the practice of signal processing contribute to and draw from a variety of disciplines: controls, communications, system identification, information theory, artificial intelligence, spectroscopy, pattern recognition, tomography, image analysis, and data acquisition, among others. To fulfill its role in these diverse areas, signal processing employs a variety of mathematical tools, including transform theory, probability, optimization, detection theory, estimation theory, numerical analysis, linear algebra, functional analysis, and many others. The practitioner of signal processing— the "signal processor"— may use several of these tools in the solution of a problem; for example, setting up a signal reconstruction algorithm, and then optimizing the parameters of the algorithm for optimum performance. Practicing signal processors must have knowledge of both the theory and the implementation of the mathematics: how and why it works, and how to make the computer do it. The breadth of mathematics employed in signal processing, coupled with the opportunity to apply that math to problems of engineering interest, makes the field both interesting and rewarding.
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