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Machine Learning Applications in Electromagnetics and Antenna Array Processing [Book Review]
IEEE Antennas and Propagation Magazine ( IF 4.2 ) Pub Date : 8-17-2022 , DOI: 10.1109/map.2022.3178921
Manel Martinez-Ramon , Arjun Gupta , Jose Luis Rojo-Alvarez , Christos Christodoulou , Kristof Cools 1
Affiliation  

Machine learning (ML) is a field of research with a rapidly growing list of applications.This book takes a unique position in bridging the gap between the ML community, on the one hand, and the electromagnetics community on the other. Classically schooled electrical engineers tend to reduce all problems to the solution of a system of linear equations. This book invites them to consider a much larger set of tools. The book is divided into two parts. Part I introduces the background and algorithms for a number of effective ML methods that lend themselves particularly well for tackling problems in the fields of electromagnetics and array processing. Part II comprises a number of chapters that start from specific problems encountered by the practicing electrical engineer. Applications range from signal analysis over antenna steering to full-wave simulation. The book is most suitable for the researcher and practitioner who wants to learn where to start in the vast domain of ML. Indeed, because of its quick development and its ongoing expansion, it can seem daunting for researchers and engineers not primarily trained in this domain to embark on its exploration. This book is a clear guide to what can be expected from ML, what the prerequisites for tackling the topic are, and what references to turn to for in-depth exposition. Teachers looking to update more traditional courses in electrical engineering will find a good starting point in this book to consider modifications to the curriculum. What is missing to simply use this book as a textbook is a comprehensible set of exercises, especially at undergraduate level.

中文翻译:


机器学习在电磁学和天线阵列处理中的应用[书评]



机器学习 (ML) 是一个应用范围快速增长的研究领域。本书在弥合 ML 社区与电磁学社区之间的差距方面具有独特的地位。受过经典教育的电气工程师倾向于将所有问题简化为线性方程组的求解。本书邀请他们考虑更多的工具。本书分为两部分。第一部分介绍了许多有效的机器学习方法的背景和算法,这些方法特别适合解决电磁学和阵列处理领域的问题。第二部分由多个章节组成,从实践电气工程师遇到的具体问题开始。应用范围从天线转向信号分析到全波仿真。本书最适合想要学习机器学习广阔领域从哪里开始的研究人员和实践者。事实上,由于其快速发展和持续扩张,对于未受过该领域主要培训的研究人员和工程师来说,开始探索似乎令人畏惧。本书清晰地介绍了 ML 的期望、解决该主题的先决条件以及深入阐述所需的参考资料。希望更新更传统的电气工程课程的教师会在本书中找到一个很好的起点来考虑对课程进行修改。仅仅将本书用作教科书所缺少的是一套易于理解的练习,尤其是对于本科水平的练习。
更新日期:2024-08-26
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