Journal ArticleDOI
EM-based optimization of microwave circuits using artificial neural networks: the state-of-the-art
Reads0
Chats0
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.read more
Citations
More filters
Journal ArticleDOI
Space mapping: the state of the art
John W. Bandler,Qingsha S. Cheng,S.A. Dakroury,Ahmed S.A. Mohamed,Mohamed H. Bakr,Kaj Madsen,Jacob Søndergaard +6 more
TL;DR: For the first time, a mathematical motivation is presented and SM is placed into the context of classical optimization to achieve a satisfactory solution with a minimal number of computationally expensive "fine" model evaluations.
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
A Space-Mapping Framework for Engineering Optimization—Theory and Implementation
TL;DR: A comprehensive approach to engineering design optimization exploiting space mapping (SM) using a new generalization of implicit SM to minimize the misalignment between the coarse and fine models of the optimized object over a region of interest.
Book ChapterDOI
Surrogate-Based Methods
TL;DR: This chapter briefly describes the basics of surrogate-based optimization, various ways of creating surrogate models, as well as several examples of surrogate -based optimization techniques.
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.
References
More filters
Journal ArticleDOI
A hierarchical neural network approach to the development of a library of neural models for microwave design
TL;DR: A hierarchical neural network framework is presented utilizing the knowledge of basic relationships common to all library components that improves the reliability of neural models, while significantly reducing the cost of library development through reduced need for data collection and shortened time of training.
Journal ArticleDOI
Design optimization of interdigital filters using aggressive space mapping and decomposition
TL;DR: This paper presents a new electromagnetic (EM) design methodology which combines two powerful techniques in a coherent strategy: space mapping (SM) and decomposition, and applies it to interdigital filter design.
Proceedings ArticleDOI
A hierarchical neural network approach to the development of library of neural models for microwave design
TL;DR: In this article, a hierarchical neural network framework is presented utilizing the knowledge of basic relationships common to all library components, which improves the reliability of neural models, while significantly reducing the cost of library development through reduced need for data collection and shortened time of training.
Journal ArticleDOI
Reverse modeling of microwave circuits with bidirectional neural network models
TL;DR: A neural network-based microwave circuit-design approach that implements the solution-searching optimization routine by a modified neural network learning process and can take advantage of a hardware neural network processor, which is significantly faster than a software simulation.
Journal ArticleDOI
Calculation of bandwidth for electrically thin and thick rectangular microstrip antennas with the use of multilayered perceptrons
TL;DR: A new, simple approach for calculating bandwidth of electrically thin and thick rectangular microstrip patch antennas, based on multilayered perceptrons network, is presented.