Statistical Signal Processing in Engineering

版本说明：1

作     者：Umberto Spagnolini 

I S B N：(纸本) 9781119293972 

出 版 社：John Wiley & Sons Ltd. 

出 版 年：2017年

主 题 词：signal processing digital signal processing statistical signal processing statistical signal processing techniques statistical signal processing algorithms theory of improper signals theory of noncircular signals statistical signal processing basic concepts statistical signal processing fundamentals statistical signal processing with matlab statistical signal processing applications statistical signal processing machine learning distributed computations for statistical signal processing distributed signal processing linear algebraic systems for statistical signal processing random variables in statistical signal processing estimation theory in statistical signal processing parameter estimation for statistical signal processing monte carlo simulations for statistical signal processing bayesian estimation for statistical signal processing spectral analysis in statistical signal processing 

学科分类：0711[理学-系统科学] 07[理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 

摘      要：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 numero