Artificial neural networks for microwave computer-aided design: The state of the art

F Feng, W Na, J Jin, J Zhang, W Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This article presents an overview of artificial neural network (ANN) techniques for a
microwave computer-aided design (CAD). ANN-based techniques are becoming useful for …

Deep neural network technique for high-dimensional microwave modeling and applications to parameter extraction of microwave filters

J Jin, C Zhang, F Feng, W Na, J Ma… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
This article introduces the deep neural network method into the field of high-dimensional
microwave modeling. Deep learning is nowadays highly successful in solving complex and …

Machine learning meets communication networks: Current trends and future challenges

I Ahmad, S Shahabuddin, H Malik, E Harjula… - IEEE …, 2020 - ieeexplore.ieee.org
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …

Recent advances in neural network‐based inverse modeling techniques for microwave applications

J Jin, F Feng, W Na, S Yan, W Liu… - … Journal of Numerical …, 2020 - Wiley Online Library
Inverse modeling of microwave components plays an important role in microwave design
and diagnosis or tuning. Since the analytical function or formula of the inverse input‐output …

A comparative analysis of behavioral models for RF power amplifiers

M Isaksson, D Wisell, D Ronnow - IEEE transactions on …, 2006 - ieeexplore.ieee.org
A comparative study of nonlinear behavioral models with memory for radio-frequency power
amplifier (PAs) is presented. The models are static polynomial, parallel Hammerstein (PH) …

Neural network inverse modeling and applications to microwave filter design

H Kabir, Y Wang, M Yu… - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
In this paper, systematic neural network modeling techniques are presented for microwave
modeling and design using the concept of inverse modeling where the inputs to the inverse …

Smart modeling of microwave devices

H Kabir, L Zhang, M Yu, PH Aaen… - IEEE Microwave …, 2010 - ieeexplore.ieee.org
Modeling and computer-aided design (CAD) techniques are essential for microwave design,
especially with the drive towards first-pass design success. We have described neural …

Physically inspired neural network model for RF power amplifier behavioral modeling and digital predistortion

F Mkadem, S Boumaiza - IEEE Transactions on Microwave …, 2011 - ieeexplore.ieee.org
In this paper, a novel two hidden layers artificial neural network (2HLANN) model is
proposed to predict the dynamic nonlinear behavior of wideband RF power amplifiers (PAs) …

A ray launching-neural network approach for radio wave propagation analysis in complex indoor environments

L Azpilicueta, M Rawat, K Rawat… - … on Antennas and …, 2014 - ieeexplore.ieee.org
A novel deterministic approach to model the radio wave propagation channels in complex
indoor environments reducing computational complexity is proposed. This technique …

Equivalent circuit theory-assisted deep learning for accelerated generative design of metasurfaces

Z Wei, Z Zhou, P Wang, J Ren, Y Yin… - … on Antennas and …, 2022 - ieeexplore.ieee.org
In this article, we propose an equivalent circuit theory-assisted deep learning approach to
accelerate the design of metasurfaces. By combining the filter equivalent circuit theory and a …