Statistical Signal Processing in Engineering
- 6h 57m
- Umberto Spagnolini
- John Wiley & Sons (UK)
- 2018
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.
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.
In this Book
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List of Abbreviations
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How to Use the Book
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Prerequisites
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Why are There So Many Matrixes in This Book?
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Manipulations on Matrixes
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Linear Algebraic Systems
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Random Variables in Brief
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Random Processes and Linear Systems
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Models and Applications
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Estimation Theory
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Parameter Estimation
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Cramér–Rao Bound
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MLE and CRB for Some Selected Cases
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Numerical Analysis and Montecarlo Simulations
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Bayesian Estimation
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Optimal Filtering
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Bayesian Tracking and Kalman Filter
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Spectral Analysis
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Adaptive Filtering
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Line Spectrum Analysis
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Equalization in Communication Engineering
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2D Signals and Physical Filters
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Array Processing
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Multichannel Time of Delay Estimation
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Tomography
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Cooperative Estimation
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Classification and Clustering
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References
