Machine Learning Applications in Electromagnetics and Antenna Array Processing [Book Review]

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.