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The Complete, Modern Guide to Developing Well-Performing Signal Processing Algorithms
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In Fundamentals of Statistical Signal Processing, Volume III: Practical Algorithm Development, author Steven M. Kay shows how to convert theories of statistical signal processing estimation and detection into software algorithms that can be implemented on digital computers. This final volume of Kay’s three-volume guide builds on the comprehensive theoretical coverage in the first two volumes. Here, Kay helps readers develop strong intuition and expertise in designing well-performing algorithms that solve real-world problems.
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Kay begins by reviewing methodologies for developing signal processing algorithms, including mathematical modeling, computer simulation, and performance evaluation. He links concepts to practice by presenting useful analytical results and implementations for design, evaluation, and testing. Next, he highlights specific algorithms that have “stood the test of time,” offers realistic examples from several key application areas, and introduces useful extensions. Finally, he guides readers through translating mathematical algorithms into MATLAB� code and verifying solutions.
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Topics covered include
- Step by step approach to the design of algorithms
- Comparing and choosing signal and noise models
- Performance evaluation, metrics, tradeoffs, testing, and documentation
- Optimal approaches using the “big theorems”
- Algorithms for estimation, detection, and spectral estimation
- Complete case studies: Radar Doppler center frequency estimation, magnetic signal detection, and heart rate monitoring
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Exercises are presented throughout, with full solutions, and executable MATLAB code that implements all the algorithms, is provided on the accompanying CD.
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This new volume is invaluable to engineers, scientists, and advanced students in every discipline that relies on signal processing; researchers will especially appreciate its timely overview of the state of the practical art. Volume III complements Dr. Kay’s Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory (Prentice Hall, 1993; ISBN-13: 978-0-13-345711-7), and Volume II: Detection Theory (Prentice Hall, 1998; ISBN-13: 978-0-13-504135-2).
- Sales Rank: #404684 in Books
- Brand: Brand: Prentice Hall
- Published on: 2013-04-05
- Original language: English
- Number of items: 1
- Dimensions: 9.47" h x 1.29" w x 7.38" l, 2.07 pounds
- Binding: Hardcover
- 496 pages
- Used Book in Good Condition
About the Author
Steven M. Kay is one of the world’s leading experts in statistical signal processing. Currently Professor of Electrical Engineering at the University of Rhode Island, Kingston, he has consulted for numerous industrial concerns, the Air Force, Army, and Navy, and has taught short courses to scientists and engineers at NASA and the CIA. Dr. Kay is a Fellow of the IEEE, and a member of Tau Beta Pi, and Sigma Xi and Phi Kappa Phi. He has received the Education Award for “outstanding contributions in education and in writing scholarly book and texts…” from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.
Most helpful customer reviews
8 of 8 people found the following review helpful.
How to approach signal processing problems
By Amazon Customer
I used Dr. Kay's other two textbooks in classes during graduate school quite a few years ago. Those two were a bit theoretical, but established a very good groundwork. This textbook is more practical, including a section on just generally how to approach signal processing or analysis problems. I have used that section to teach some undergrads how to approach this type of problem.
Aside from the above, my primary goal with this book is to find any useful "rules of thumb", or "gems" that make data analysis or signal processing easier to do practically. So far, I am only about a quarter through the book (I'm just reading as I have time). One point that I have learned from the book was how there are no free lunches. There is a tradeoff between more robust approaches and more optimal versions that may take advantage of a priori information. I may have known that intuitively, but not as explicitly as I did previous to this book.
2 of 8 people found the following review helpful.
Perfect
By Christian Reyes
Very good service and product.
Book has a complete information about modulation theory.
I recommend this book for students of telecommunications
2 of 7 people found the following review helpful.
Five Stars
By yjoon
good
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