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:
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
Artificial neural networks for RF and microwave design - from theory to practice
TL;DR: Fundamental concepts in this emerging area of neural-network computational modules are described at teaching RF/microwave engineers what neural networks are, why they are useful, when they can be used, and how to use them.
Journal ArticleDOI
Deep learning for the design of photonic structures
TL;DR: Recent progress in deep-learning-based photonic design is reviewed by providing the historical background, algorithm fundamentals and key applications, with the emphasis on various model architectures for specific photonic tasks.
Journal Article
Space mapping
TL;DR: A generic space-mapping optimization algorithm is formulated, explained step-by-step using a simple microstrip filter example, and its robustness is demonstrated through the fast design of an interdigital filter.
Journal ArticleDOI
EM-based optimization of microwave circuits using artificial neural networks: the state-of-the-art
Abstract: 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-based design of microwave circuits using ANNs is also reviewed. The conventional microwave neural optimization approach is surveyed, along with typical enhancing techniques, such as segmentation, decomposition, hierarchy, design of experiments, and clusterization. Innovative strategies for ANN-based design exploiting microwave knowledge are reviewed, including neural space-mapping methods. The problem of developing synthesis neural networks is treated. EM-based statistical analysis and yield optimization using neural networks is reviewed. The key issues in transient EM-based design using neural networks are summarized. The use of ANNs to speed up "global modeling" for EM-based design of monolithic microwave integrated circuits is briefly described. Future directions in ANN techniques to microwave design are suggested.
Journal ArticleDOI
Neural Network Inverse Modeling and Applications to Microwave Filter Design
TL;DR: In this article, a neural network inverse model is proposed for microwave modeling and design using the concept of inverse modeling where the inputs to the inverse model are electrical parameters and outputs are geometrical parameters.
References
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Journal ArticleDOI
Artificial neural networks in manufacturing: concepts, applications, and perspectives
Samuel H. Huang,Hong-Chao Zhang +1 more
TL;DR: The aim of the authors is to provide useful guidelines and references for the research and implementation of artificial neural networks in the field of manufacturing.
Journal ArticleDOI
A large-signal, analytic model for the GaAs MESFET
M.A. Khatibzadeh,Robert J. Trew +1 more
TL;DR: In this article, an analytic large-signal model for the GaAs MESFET is presented, which describes the conduction and displacement currents of the FET as a function of instantaneous terminal voltages and their time derivatives.
Journal ArticleDOI
Nonlinear circuit analysis using the method of harmonic balance—a review of the art. II. Advanced 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.
Journal ArticleDOI
Efficient quadratic approximation for statistical design
TL;DR: In this paper, a highly efficient approach to quadratic approximation of circuit responses is presented, which uses a fixed pattern of base points and requires extremely small amounts of CPU time and storage space.
Journal ArticleDOI
Fast and smooth highly nonlinear multidimensional table models for device modeling
TL;DR: In this paper, a general scheme for the construction of device models for circuit simulators is presented, which can automatically reconstruct the exact DC current behavior of two basic physical device models, namely, the Ebers-Moll bipolar transistor model and the GLASMOST MOSFET model.