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 algebra, optimization, and statistical signal processing.
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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 he has served on the faculty since 1984. He received his Ph.D. in electrical engineering from Stanford University, and has worked as a research engineer for Rockwell International Corporation, ESL, Inc. (now TRW), and Autonetics. His research interests include decision theory, control theory, estimation theory, and stochastic processes. Dr. Stirling has contributed numerous articles to professional journals, and is a member of IEEE and Phi Beta Kappa.
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.
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