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Artificial Neural Networks for Parametric Electromagnetic Modeling and Optimization by Feng Feng; Weicong Na; Jing Jin; Qi‐Jun Zhang is a book available to read on EtoBox.

What is Artificial Neural Networks for Parametric Electromagnetic Modeling and Optimization about?

Parametric electromagnetic (EM) modeling and optimization techniques are integral parts of the field of microwave design. Parametric models can be constructed based on the relationship between EM response and geometric variables. The constructed parametric model enables rapid simulation and optimization using different geometric variables, which can then be used in high-standard designs. Artificial neural network (ANN) is a common technique for parameterized modeling and optimization of the design [1][2][3][4][5][6][7][8][9]. With proper training, ANN can characterize the relationship between EM responses and geometric variables. After the training process, ANN can provide rapid and precise predictions of the EM performances in passive elements; furthermore, it can be exploited in succeeding high-standard design of microwave circuits. Over the past few decades, ANN has been applied to parametric EM modeling and optimization of various microwave circuits . A deep neural network (DNN) refers to a neural network with multiple hidden layers [33]. While modeling very complicated daedal relationships, such as modeling with high-dimensional filters with many input variables, DNNs have bet

Author

Feng Feng; Weicong Na; Jing Jin; Qi‐Jun Zhang

Publisher

Wiley & Sons, Incorporated, John

Published

2023

Language

EN

ISBN

9781119853893