Statistical Signal Processing in Engineering - by Umberto Spagnolini (Hardcover)

Book Synopsis

A problem-solving approach to statistical signal processing for practicing engineers, technicians, and graduate students

This book takes a pragmatic approach in solving a set of common problems engineers and technicians encounter when processing signals. In writing it, the author drew on his vast theoretical and practical experience in the field to provide a quick-solution manual for technicians and engineers, offering field-tested solutions to most problems engineers can encounter. At the same time, the book delineates the basic concepts and applied mathematics underlying each solution so that readers can go deeper into the theory to gain a better idea of the solution's limitations and potential pitfalls, and thus tailor the best solution for the specific engineering application.

Uniquely, Statistical Signal Processing in Engineering can also function as a textbook for engineering graduates and post-graduates. Dr. Spagnolini, who has had a quarter of a century of experience teaching graduate-level courses in digital and statistical signal processing methods, provides a detailed axiomatic presentation of the conceptual and mathematical foundations of statistical signal processing that will challenge students' analytical skills and motivate them to develop new applications on their own, or better understand the motivation underlining the existing solutions.

Throughout the book, some real-world examples demonstrate how powerful a tool statistical signal processing is in practice across a wide range of applications.

• Takes an interdisciplinary approach, integrating basic concepts and tools for statistical signal processing
• Informed by its author's vast experience as both a practitioner and teacher
• Offers a hands-on approach to solving problems in statistical signal processing
• Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering and distributed computations
• Features numerous real-world examples from a wide range of applications showing the mathematical concepts involved in practice
• Includes MATLAB code of many of the experiments in the book

Statistical Signal Processing in Engineering is an indispensable working resource for electrical engineers, especially those working in the information and communication technology (ICT) industry. It is also an ideal text for engineering students at large, applied mathematics post-graduates and advanced undergraduates in electrical engineering, applied statistics, and pure mathematics, studying statistical signal processing.

From the Back Cover

A Problem-Solving Approach to Statistical Signal Processing for Practicing Engineers, Technicians, and Graduate Students

This reference takes a pragmatic approach to solving a set of common problems encountered by engineers and technicians when processing signals. Drawing on the author's vast theoretical and practical experience, it offers field-tested solutions to most problems engineers and technicians can encounter. At the same time, it delineates the basic concepts and applied mathematics underlying each solution so that readers can go deeper into the theory to gain a better idea of the solution's limitations and potential pitfalls, thus tailoring the best solution for specific engineering applications.

Statistical Signal Processing in Engineering also functions as a text for engineering graduate students. Dr. Spagnolini, who has 25 years' experience teaching graduate-level courses in digital and statistical signal processing methods, provides a detailed axiomatic presentation of the conceptual and mathematical foundations of statistical signal processing. This will challenge students' analytical skills and motivate them to develop their own new applications as well as understand the motivation underlining existing solutions.

This unique work

• Takes an interdisciplinary approach, integrating basic concepts and tools for statistical signal processing
• Offers a hands-on approach to solving problems in statistical signal processing
• Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering and distributed computations
• Features numerous real-world examples across wide ranging applications to illustrate mathematical concepts involved in practice
• Includes MATLAB code of many of the experiments in the book

Statistical Signal Processing in Engineering is an indispensable working resource for electrical engineers, especially those working in the information and communication technology (ICT) industry. It is also an invaluable text for electrical engineering, applied statistics, and mathematics graduate and advanced undergraduate students studying statistical signal processing.

About the Author

UMBERTO SPAGNOLINI is Professor in Signal Processing and Telecommunications at Politecnico di Milano, Italy. Prof. Spagnolini's research focuses on statistical signal processing, communication systems, and advanced topics in signal processing for remote sensing and wireless communication systems. He is a Senior Member of the IEEE, engages in editorial activity for IEEE journals and conferences, and has authored 300 patents and papers in peer reviewed journals and conferences.