A problem-solving approach to statisticalsignalprocessing for practicing engineers, technicians, and graduate students This book takes a pragmatic approach in solving a set of common problems engineers and technicia...
详细信息
ISBN:
(数字)9781119294016
ISBN:
(纸本)9781119293972
A problem-solving approach to statisticalsignalprocessing 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 processingsignals. 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, statisticalsignalprocessing 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 statisticalsignalprocessing methods, provides a detailed axiomatic presentation of the conceptual and mathematical foundations of statisticalsignalprocessing 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 statisticalsignalprocessing is in practice across a wide range of applications. Takes an interdisciplinary approach, integrating basic concepts and tools for statisticalsignalprocessing Informed by its author’s vast experience as both a practitioner and teacher Offers a hands-on approach to solving problems in statisticalsignalprocessing Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering and distributed computations Features numero
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