Machine learning techniques in analog/RF integrated circuit design, synthesis, layout, and test

E Afacan, N Lourenço, R Martins, G Dündar - Integration, 2021 - Elsevier
Rapid developments in semiconductor technology have substantially increased the
computational capability of computers. As a result of this and recent developments in theory …

EM-based optimization of microwave circuits using artificial neural networks: The state-of-the-art

JE Rayas-Sánchez - IEEE Transactions on Microwave Theory …, 2004 - ieeexplore.ieee.org
This paper reviews the current state-of-the-art in electromagnetic (EM)-based design and
optimization of microwave circuits using artificial neural networks (ANNs). Measurement …

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 …

Artificial neural networks for RF and microwave design-from theory to practice

QJ Zhang, KC Gupta… - IEEE transactions on …, 2003 - ieeexplore.ieee.org
Neural-network computational modules have recently gained recognition as an
unconventional and useful tool for RF and microwave modeling and design. Neural …

A review on the artificial neural network applications for small‐signal modeling of microwave FETs

Z Marinković, G Crupi, A Caddemi… - … Journal of Numerical …, 2020 - Wiley Online Library
The purpose of this paper is to provide a comprehensive overview of the field‐effect
transistor (FET) small‐signal modeling using artificial neural networks (ANNs). To gain an in …

Neural-based dynamic modeling of nonlinear microwave circuits

J Xu, MCE Yagoub, R Ding… - IEEE Transactions on …, 2002 - ieeexplore.ieee.org
A neural network formulation for modeling nonlinear microwave circuits is achieved in the
most desirable format, ie, continuous time-domain dynamic system format. The proposed …

A robust algorithm for automatic development of neural-network models for microwave applications

VK Devabhaktuni, MCE Yagoub… - IEEE Transactions on …, 2001 - ieeexplore.ieee.org
For the first time, we propose a robust algorithm for automating the neural-network-based
RF/microwave model development process. Starting with zero amount of training data and …

Advanced microwave modeling framework exploiting automatic model generation, knowledge neural networks, and space mapping

VK Devabhaktuni, B Chattaraj… - IEEE Transactions …, 2003 - ieeexplore.ieee.org
In this paper, we propose an efficient knowledge-based automatic model generation
(KAMG) technique aimed at generating microwave neural models of the highest possible …

Extraction and use of neural network models in automated synthesis of operational amplifiers

G Wolfe, R Vemuri - … Transactions on Computer-Aided Design of …, 2003 - ieeexplore.ieee.org
Fast and accurate performance estimation methods are essential to automated synthesis of
analog circuits. Development of analog performance models is difficult due to the highly …

Applications of artificial neural networks in optical performance monitoring

X Wu, JA Jargon, RA Skoog, L Paraschis… - Journal of Lightwave …, 2009 - opg.optica.org
Applications using artificial neural networks (ANNs) for optical performance monitoring
(OPM) are proposed and demonstrated. Simultaneous identification of optical signal-to …