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Statistical Signal Processing in Engineering
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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.
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