Applications of Neural Networks in Electromagnetics FROM THE PUBLISHER
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. Organized in a modular format that lets you find and use the information you need fast, the book includes five full chapters that zero-in on specific neural network applications. Included are chapters on antennas, remote sensing and target classification, microwave devices and circuit modeling, and real-time performance systems for military and civilian systems, such as GPS and mobile communications. You also see how neural networks can be used in conjunction with other methods, such as the finite element method, the finite difference method, and the method of moments. More than 700 equations and over 200 illustrations are included, and MATLAB code for applications using neural network technology is found in relevant chapters.
FROM THE CRITICS
Booknews
Since the early 1990s, many electromagnetic problems have been solved using neural networks. However, due to the perceived separation between the fields, few electromagneticists are aware of the possibilities of neural networks. This book aims to bridge the gap by explaining numerous neural network architectures and how they have been used to solve various electromagnetic problems. Through comparison with classical solutions, the merits of the method are demonstrated. Theories of single and multilayer perceptron networks, radial basis function networks, Kohonen networks, adaptive resonance theory neural networks and recurrent neural networks are explored extensively, and applications in antennas, radar and remote sensing, mobile communications, microwave circuits and devices, and computational electromagnetics are discussed. Annotation c. Book News, Inc., Portland, OR (booknews.com)
AUTHOR DESCRIPTION
Christos G. Christodoulou is professor and chair of the Department of Electrical and Computer Engineering at the University of New Mexico. He is co-editor of a column on wireless communications for the IEEE AP magazine. He holds an M.S. and a Ph.D. in Electrical Engineering from North Carolina State University.
Michael Georgiopoulos is an associate professor in the Department of Electrical and Computer Engineering at the University of New Mexico. The author of more than 90 papers on theoretical and application issues pertaining to neural networks, he holds an M.S. and a Ph.D. in Electrical Engineering from the University of Connecticut at Storrs.
ACCREDITATION
Christos G. Christodoulou is professor and chair of the Department of Electrical and Computer Engineering at the University of New Mexico. He is co-editor of a column on wireless communications for the IEEE AP magazine. He holds an M.S. and a Ph.D. in Electrical Engineering from North Carolina State University. Michael Georgiopoulos is an associate professor in the Department of Electrical and Computer Engineering at the University of New Mexico. The author of more than 90 papers on theoretical and application issues pertaining to neural networks, he holds an M.S. and a Ph.D. in Electrical Engineering from the University of Connecticut at Storrs.
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