Machine learning applications in electromagnetics and antenna array processing

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 optimizatio...

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Bibliographic Details
Main Author: Martínez-Ramón, Manel, 1968- (Author)
Format: eBook
Language: English
Published: Boston : Artech House, [2021]
Series: Artech House electromagnetic analysis series.
Subjects:
Machine learning.
elektronické knihy
electronic books
ISBN: 9781630817763
1630817767
1630817759
9781630817756
Physical Description: 1 online resource (xiii, 331 pages)

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Table of contents

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020 |a 9781630817763  |q (electronic bk.) 
020 |a 1630817767  |q (electronic bk.) 
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035 |a (OCoLC)1260220722  |z (OCoLC)1280072168 
100 1 |a Martínez-Ramón, Manel,  |d 1968-  |e author.  |1 https://id.oclc.org/worldcat/entity/E39PCjJqfg7MwMCcbkQK43jh6q 
245 1 0 |a Machine learning applications in electromagnetics and antenna array processing /  |c Manel Martínez-Ramón, Arjun Gupta, José Luis Rojo-Álvarez, Christos Christodoulou. 
264 1 |a Boston :  |b Artech House,  |c [2021] 
300 |a 1 online resource (xiii, 331 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Artech House electromagnetic series 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a 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. 
504 |a Includes bibliographical references. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Machine learning. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version:  |a Martínez-Ramón, Manel, 1968-  |t Machine learning applications in electromagnetics and antenna array processing.  |d Boston : Artech House, [2021]  |z 1630817759  |w (OCoLC)1237307871 
830 0 |a Artech House electromagnetic analysis series. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpMLAEAAPN/machine-learning-applications?kpromoter=marc  |y Full text 

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