Journal ArticleDOI
A neural network modeling approach to circuit optimization and statistical design
TLDR
This paper presents a new approach to microwave circuit optimization and statistical design featuring neural network models at either device or circuit levels, which has the capability to handle high-dimensional and highly nonlinear problems.Abstract:Â
The trend of using accurate models such as physics-based FET models, coupled with the demand for yield optimization results in a computationally challenging task. This paper presents a new approach to microwave circuit optimization and statistical design featuring neural network models at either device or circuit levels. At the device level, the neural network represents a physics-oriented FET model yet without the need to solve device physics equations repeatedly during optimization. At the circuit level, the neural network speeds up optimization by replacing repeated circuit simulations. This method is faster than direct optimization of original device and circuit models. Compared to existing polynomial or table look-up models used in analysis and optimization, the proposed approach has the capability to handle high-dimensional and highly nonlinear problems. >read more
Citations
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Journal ArticleDOI
Knowledge-based neural models for microwave design
Fang Wang,Qi-Jun Zhang +1 more
TL;DR: A new microwave-oriented knowledge based neural network is proposed, in which microwave knowledge in the form of empirical functions or analytical approximations are incorporated into neural networks that enhances neural model accuracy especially for unseen data and reduces the need of large set of training data.
Journal ArticleDOI
EM-ANN models for microstrip vias and interconnects in dataset circuits
P.M. Watson,K.C. Gupta +1 more
TL;DR: A novel approach for accurate and efficient modeling of monolithic microwave/millimeter wave integrated circuit (MMIC) components by using electromagnetically trained artificial neural network (EM-ANN) software modules is presented.
Journal ArticleDOI
Neuromodeling of microwave circuits exploiting space-mapping technology
TL;DR: In this paper, the authors presented modeling of microwave circuits using artificial neural networks (ANN's) based on space-mapping (SM) technology, which decrease the cost of training, improve generalization ability, and reduce the complexity of the ANN topology with respect to the classical neuromodeling approach.
Journal ArticleDOI
Deep neural networks for the evaluation and design of photonic devices
TL;DR: In this paper, the authors show how deep neural networks, configured as discriminative networks, can learn from training sets and operate as high-speed surrogate electromagnetic solvers, inverse modelling tools and global device optimizers, and how deep generative networks can learn geometric features in device distributions and even be configured to serve as robust global optimizers.
Journal ArticleDOI
Smart Modeling of Microwave Devices
TL;DR: This work has described neural networks for microwave modeling and design and demonstrated that neural networks are helpful in developing parametric or scalable models for passive and active microwave devices.
References
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TL;DR: In this paper, a new method for the solution of nonlinear periodic networks has been developed, where the network is decomposed into a minimum number of linear and nonlinear subnetworks.
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State of the art and present trends in nonlinear microwave CAD techniques
Vittorio Rizzoli,Andrea Neri +1 more
TL;DR: A survey of modern nonlinear CAD techniques as applied to the specific field of microwave circuits shows that the various subjects are not just separate items, but rather can be chained in a strictly logical sequence.
Journal ArticleDOI
Circuit optimization: the state of the art
John W. Bandler,S.H. Chen +1 more
TL;DR: A unified hierarchical treatment of circuit models forms the basis of the presentation, and the concepts of design centering, tolerance assignment, and postproduction tuning in relation to yield enhancement and cost reduction suitable for integrated circuits are discussed.
Journal ArticleDOI
Nonlinear circuit analysis using the method of harmonic balance—A review of the art. Part I. Introductory concepts
TL;DR: The harmonic balance method is a technique for the numerical solution of nonlinear analog circuits operating in a periodic, or quasi-periodic, steady-state regime as mentioned in this paper, which can be used to efficiently derive the continuous-wave response of numerous nonlinear microwave components including amplifiers, mixers, and oscillators.