Overview
- Self-contained, deliberately compact, and user-friendly textbook
- Many diverse examples as well as end-of-chapter problems and exercises
- Computer simulation algorithms to reinforce the theory presented
- Accessible to a broad audience of junior/senior undergraduates or graduate students in electrical, systems, computer, and biomedical engineering, as well as the physical sciences
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Table of contents (9 chapters)
Reviews
“A First Course in Statistics for Signal Analysis is a small, dense, and inexpensive book that covers exactly what the title says: statistics for signal analysis. The book is targeted at classes ‘mainly populated by electrical, systems, computer and biomedical engineering juniors/seniors and graduate students…’ The book has much to recommend it. The author clearly understands the topics presented. The topics are covered in a rigorous manner, but not so rigorous as to be ostentatious. The sequence of topics is clearly targeted at the spectral properties of Gaussian stationary signals. Any student studying traditional communications and signal processing would benefit from an understanding of these topics…In summary, A First Course in Statistics for Signal Analysis has much in its favor. It is short, rigorous, mostly free of typos, and inexpensive…This book is most appropriate for a graduate class in signal analysis. It also could be used as a secondary text in a statistics, signal processing, or communications class.” —JASA
Authors and Affiliations
Bibliographic Information
Book Title: A First Course in Statistics for Signal Analysis
Authors: Wojbor A. Woyczyński
DOI: https://doi.org/10.1007/978-0-8176-4516-8
Publisher: Birkhäuser Boston, MA
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Birkhäuser Boston 2006
eBook ISBN: 978-0-8176-4516-8Published: 26 May 2007
Edition Number: 1
Number of Pages: XIV, 208
Number of Illustrations: 65 b/w illustrations
Topics: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Signal, Image and Speech Processing, Fourier Analysis, Probability Theory and Stochastic Processes