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This essentially self-contained, deliberately compact, and user-friendly textbook is designed for a first, one-semester course in statistical signal analysis for a broad audience of students in engineering and the physical sciences. The emphasis throughout is on fundamental concepts and relationships in the statistical theory of stationary random signals, explained in a concise, yet fairly rigorous presentation.
New to the Second Edition: many redrawn figures to better illustrate the scale of the quantities represented; revised notation and terminology to better reflect the concepts under discussion; considerably expanded sections with new examples, illustrations, and commentary; addition of more applied exercises; a large appendix containing solutions of selected problems from each of the nine chapters.
Developed by the author over the course of many years of classroom use, A First Course in Statistics for Signal Analysis may be used by junior/senior undergraduates or graduate students in electrical, systems, computer, and biomedical engineering, as well as the physical sciences. The work is also an excellent resource of educational and training material for scientists and engineers working in research laboratories.
'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 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, [the work] has much in its favor.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 (Review of the First Edition)
From the reviews of the second edition:
"This is nicely written self-contained book and it is a good candidate for adoption as a textbook for upper-level undergraduate and even for a graduate course for engineering and physical sciences students. . One of the nicest features of this book is the bibliographical comments given before the index, providing comprehensive developments of the material in chronological order. In summary, it is well-written and, most importantly, a well-priced book. I have no hesitation in recommending it as a textbook for the targeted course and audience." (Technometrics, Vol. 53 (4), November, 2011)
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