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
Polynomial Chaos-Based Approach to Yield-Driven EM Optimization
TL;DR: The use of polynomial chaos (PC) approach from electromagnetic (EM)-based yield estimation to EM-based yield optimization of microwave structures is extended and the advantages are demonstrated by yield-driven EM optimization of three waveguide filter examples.
Journal ArticleDOI
Robust Parametric Macromodeling Using Multivariate Orthonormal Vector Fitting
TL;DR: A robust multivariate extension of the orthonormal vector fitting technique is introduced for rational parametric macromodeling of highly dynamic responses in the frequency domain.
Journal ArticleDOI
Exact adjoint sensitivity analysis for neural-based microwave modeling and design
TL;DR: For the first time, an adjoint neural network method is introduced for sensitivity analysis in neural-based microwave modeling and design and allows the models to learn both the input/output behavior of the modeling problem and its derivative data simultaneously.
Journal ArticleDOI
Creating accurate multivariate rational interpolation models of microwave circuits by using efficient adaptive sampling to minimize the number of computational electromagnetic analyses
Robert Lehmensiek,Petrie Meyer +1 more
TL;DR: A variation of the standard BCF that uses approximation to establish a nonrectangular grid of support points that systematically increases the order by optimally choosing new support points in the areas of highest error until the required accuracy is achieved.
Journal ArticleDOI
Empirical decision model learning
TL;DR: This paper proposes a methodology called Empirical Model Learning (EML) that relies on Machine Learning for obtaining components of a prescriptive model, using data either extracted from a predictive model or harvested from a real system, and uses two learning methods, namely Artificial Neural Networks and Decision Trees.
References
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Journal ArticleDOI
A piecewise harmonic balance technique for determination of periodic response of nonlinear systems
M. Nakhla,J. Vlach +1 more
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.
Journal ArticleDOI
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.