Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning
About this book
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning
Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The content of the book covers all-dielectric and metallodielectric optical metasurface deep learning-accelerated inverse-design, deep neural networks for inverse scattering, applications of deep learning for advanced antenna design, and other related topics.
To aid in reader comprehension, each chapter contains 10-15 illustrations, including prototype photos, line graphs, and electric field plots. Contributed to by leading research groups in the field, sample topics covered in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning include:
- Optical and photonic design, including generative machine learning for photonic design and inverse design of electromagnetic systems
- RF and antenna design, including artificial neural networks for parametric electromagnetic modeling and optimization and analysis of uniform and non-uniform antenna arrays
- Inverse scattering, target classification, and other applications, including deep learning for high contrast inverse scattering of electrically large structures
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning is a must-have resource on the topic for university faculty, graduate students, and engineers within the fields of electromagnetics, wireless communications, antenna/RF design, and photonics, as well as researchers at large defense contractors and government laboratories.
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Information
Table of contents
- Cover
- Table of Contents
- Title Page
- Copyright
- Dedication
- About the Editors
- List of Contributors
- Preface
- Section I: Introduction to AIāBased Regression and Classification
- Section II: Advancing Electromagnetic Inverse Design with Machine Learning
- Section III: Deep Learning for Metasurface Design
- Section IV: RF, Antenna, InverseāScattering, and Other EM Applications of Deep Learning
- Index
- End User License Agreement