Application of machine learning in electromagnetics: Mini-review
As an integral part of the electromagnetic system, antennas are becoming more advanced
and versatile than ever before, thus making it necessary to adopt new techniques to …
and versatile than ever before, thus making it necessary to adopt new techniques to …
A multilevel bottom-up optimization methodology for the automated synthesis of RF systems
In recent years there has been a growing interest in electronic design automation
methodologies for the optimization-based design of radio frequency (RF) circuits and …
methodologies for the optimization-based design of radio frequency (RF) circuits and …
DeepPlacer: a custom integrated OpAmp placement tool using deep models
Mechanisms towards the automatic analog integrated circuit layout design have been an
intensive research topic in the past few decades. Still, the industrial environment has no …
intensive research topic in the past few decades. Still, the industrial environment has no …
A surrogate-based parallel optimization of analog circuits using multi-acquisition functions
S Du, H Liu, Q Hong, C Wang - AEU-International Journal of Electronics …, 2022 - Elsevier
Surrogate-based optimization has been widely used in analog circuit sizing. Surrogate-
based optimization efficiency in a parallel computing environment has become an emerging …
based optimization efficiency in a parallel computing environment has become an emerging …
Enhanced systematic design of a voltage controlled oscillator using a two-step optimization methodology
In this paper a design strategy based on bottom-up design methodologies is used in order to
systematically design a voltage controlled oscillator. The methodology uses two computer …
systematically design a voltage controlled oscillator. The methodology uses two computer …
Accelerating Gaussian Process surrogate modeling using Compositional Kernel Learning and multi-stage sampling framework
SS Jin - Applied Soft Computing, 2021 - Elsevier
Surrogate modeling is becoming a popular tool to approximate computationally-expensive
simulations for complex engineering problems. In practice, there are still difficulties in …
simulations for complex engineering problems. In practice, there are still difficulties in …
PACOSYT: A passive component synthesis tool based on machine learning and tailored modeling strategies towards optimal RF and mm-Wave circuit designs
In this paper, the application of regression-based supervised machine learning (ML)
methods to the modeling of integrated inductors and transformers is examined. Different ML …
methods to the modeling of integrated inductors and transformers is examined. Different ML …
Convergence rates of the efficient global optimization algorithm for improving the design of analog circuits
Optimal sizing of analog circuits is a hard and time-consuming challenge. Nowadays,
analog designers are more than ever interested in developing solutions for automating such …
analog designers are more than ever interested in developing solutions for automating such …
A synthesis-analysis machine with self-inspection mechanism for automatic design of on-chip inductors based on artificial neural networks
Z Wang, F Yan, S Ma, T Yang, H Shao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
An automatic inductor design process is helpful to reduce the design cycle of radio
frequency (RF) integrated circuit (IC). This paper proposed an efficient synthesis-analysis …
frequency (RF) integrated circuit (IC). This paper proposed an efficient synthesis-analysis …
An efficient transformer modeling approach for mm-wave circuit design
In this paper, a Gaussian-process surrogate modeling methodology is used to accurately
and efficiently model transformers, which are still a bottleneck in radio-frequency and …
and efficiently model transformers, which are still a bottleneck in radio-frequency and …