Applications Of Neural Networks In Electromagnetics
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Applications of Neural Networks in Electromagnetics
Author: Christos Christodoulou
language: en
Publisher: Artech House Publishers
Release Date: 2001
The high-speed capabilities and learning abilities of neural networks can be applied to quickly solving numerous complex optimization problems in electromagnetics, and this book shows you how. Even if you have no background in neural networks, this book helps you understand the basics of each main network architecture in use today, including its strengths and limitations. Moreover, it gives you the knowledge you need to identify situations when the use of neural networks is the best problem-solving option.
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 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.
Wavelet Applications in Engineering Electromagnetics
Written from an engineering perspective, this unique resource describes the practical application of wavelets to the solution of electromagnetic field problems and in signal analysis with an even-handed treatment of the pros and cons. A key feature of this book is that the wavelet concepts have been described from the filter theory point of view that is familiar to researchers with an electrical engineering background. The book shows you how to design novel algorithms that enable you to solve electrically, large electromagnetic field problems using modest computational resources. It also provides you with new ideas in the design and development of unique waveforms for reliable target identification and practical radar signal analysis. The book includes more then 500 equations, and covers a wide range of topics, from numerical methods to signal processing aspects.