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Machine Learning Applications in Electromagnetics and Antenna Array Processing - Manel Martinez-Ramon, Arjun Gupta, Jose Luis Rojo-Alvarez, Christos Christodoulou

Machine Learning Applications in Electromagnetics and Antenna Array Processing

Buch | Hardcover
436 Seiten
2021 | Unabridged edition
Artech House Publishers (Verlag)
978-1-63081-775-6 (ISBN)
CHF 278,90 inkl. MwSt
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This practical resource provides an overview of machine learning (ML) approaches as applied to electromagnetics and antenna array processing. Detailed coverage of the main trends in ML, including uniform and random array processing (beamforming and detection of angle of arrival), antenna optimization, wave propagation, remote sensing, radar, and other aspects of electromagnetic design are explored. An introduction to machine learning principles and the most common machine learning architectures and algorithms used today in electromagnetics and other applications is presented, including basic neural networks, gaussian processes, support vector machines, kernel methods, deep learning, convolutional neural networks, and generative adversarial networks. Applications in electromagnetics and antenna array processing that are solved using machine learning are discussed, including antennas, remote sensing, and target classification.

Part I: Introduction to Machine Learning: Kernel methods for array processing; Support Vector Machines; Gaussian Processes for signal processing; Neural Networks; Convolutional neural networks; Recursive neural networks for signals; Restricted Boltzmann Machines; Generative Adversarial Networks; Part II: Applications in Electromagnetics and Antenna Array Signal Processing: Antenna Array Signal Processing; Radar and Remote Sensing; Computational Electromagnetics; Reconfigurable Antennas and Cognitive Radio; Design and Optimization of Antennas and RF devices; Wave Propagation and Modelling; Electromagnetics for Medicine and Healthcare.

Erscheinungsdatum
Verlagsort Norwood
Sprache englisch
Themenwelt Technik Elektrotechnik / Energietechnik
ISBN-10 1-63081-775-9 / 1630817759
ISBN-13 978-1-63081-775-6 / 9781630817756
Zustand Neuware
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