| Description |
1 online resource (xiii, 331 pages). |
| Physical Medium |
polychrome |
| Description |
text file |
| Series |
Artech House electromagnetic series
|
|
Artech House electromagnetic analysis series.
|
| Summary |
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. |
| Bibliography |
Includes bibliographical references. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Machine learning.
|
|
Machine learning. |
| Genre/Form |
Electronic books.
|
| Other Form: |
Print version: Martínez-Ramón, Manel, 1968- Machine learning applications in electromagnetics and antenna array processing. Boston : Artech House, [2021] 1630817759 (OCoLC)1237307871 |
| ISBN |
9781630817763 (electronic book) |
|
1630817767 (electronic book) |
|
1630817759 |
|
9781630817756 |
|
