For Senior/Graduate Level Signal Processing courses. The book is also suitable for a course in advanced signal processing, or for self-study.
Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing students and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear...
TODD K. MOON is currently with the Electrical and Computer Engineering department at Utah State University, where he has taught widely in the area of signals and systems, including signal processing, communications, controls, and information theory. His research interests have included signal separation, spread-spectrum communication, wavelet modulation, speech processing, and signal reconstruction.
WYNN C. STIRLING is a professor of electrical engineering at Brigham Young University, where...
Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear algebra, optimization, and statistical signal processing.
FEATURES/BENEFITS
Preface
Rationale
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...
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