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Evolutionary neuro-space mapping technique for modeling of nonlinear microwave devices

Dirk Gorissen UGent, Lei Zhang, Qi Jun Zhang and Tom Dhaene UGent (2011) IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. 59(2). p.213-229
abstract
This paper presents a new advance in Neuro-space mapping (Neuro-SM) techniques for modeling nonlinear microwave devices. Suppose that existing device models (namely, coarse models) cannot match the behavior of a new device (referred to as the fine model). By neural network mapping of the voltage and current signals from the coarse to the fine models, Neuro-SM can modify the behavior of the coarse model to match that of the fine model. However, the efficiency of mapping depends on both the mapping structure and the coarse model. In this paper, a structural optimization technique is presented to achieve optimal combinations of mapping structure and coarse model. An aggressive optimization formulation exploring detailed structural variations in both the mapping and the coarse model is proposed, where the internal branches of coarse models and separate mappings for the voltage and current at gate and drain are used as basic topology variables. The formulation of such a structural optimization by an evolutionary optimization algorithm is proposed. Numerical examples of metal-semiconductor field-effect transistor and high electron-mobility transistor modeling demonstrate that, by using the proposed algorithm, optimal combinations of space mapping and coarse model structures can be achieved leading to the best modeling accuracy with the simplest mapping function.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
CIRCUITS, nonlinear device modeling, FETS, SIMULATION, Genetic algorithms, knowledge-based modeling, space mapping, NETWORKS, COMPONENTS, OPTIMIZATION, GAAS-MESFET, LARGE-SIGNAL, OF-THE-ART, COMPUTER-AIDED-DESIGN
journal title
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
IEEE Trans. Microw. Theory Tech.
volume
59
issue
2
pages
213 - 229
Web of Science type
Article
Web of Science id
000287415700001
JCR category
ENGINEERING, ELECTRICAL & ELECTRONIC
JCR impact factor
1.853 (2011)
JCR rank
55/244 (2011)
JCR quartile
1 (2011)
ISSN
0018-9480
DOI
10.1109/TMTT.2010.2090169
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2132065
handle
http://hdl.handle.net/1854/LU-2132065
date created
2012-06-05 09:03:09
date last changed
2012-06-07 10:43:59
@article{2132065,
  abstract     = {This paper presents a new advance in Neuro-space mapping (Neuro-SM) techniques for modeling nonlinear microwave devices. Suppose that existing device models (namely, coarse models) cannot match the behavior of a new device (referred to as the fine model). By neural network mapping of the voltage and current signals from the coarse to the fine models, Neuro-SM can modify the behavior of the coarse model to match that of the fine model. However, the efficiency of mapping depends on both the mapping structure and the coarse model. In this paper, a structural optimization technique is presented to achieve optimal combinations of mapping structure and coarse model. An aggressive optimization formulation exploring detailed structural variations in both the mapping and the coarse model is proposed, where the internal branches of coarse models and separate mappings for the voltage and current at gate and drain are used as basic topology variables. The formulation of such a structural optimization by an evolutionary optimization algorithm is proposed. Numerical examples of metal-semiconductor field-effect transistor and high electron-mobility transistor modeling demonstrate that, by using the proposed algorithm, optimal combinations of space mapping and coarse model structures can be achieved leading to the best modeling accuracy with the simplest mapping function.},
  author       = {Gorissen, Dirk and Zhang, Lei and Zhang, Qi Jun and Dhaene, Tom},
  issn         = {0018-9480},
  journal      = {IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES},
  keyword      = {CIRCUITS,nonlinear device modeling,FETS,SIMULATION,Genetic algorithms,knowledge-based modeling,space mapping,NETWORKS,COMPONENTS,OPTIMIZATION,GAAS-MESFET,LARGE-SIGNAL,OF-THE-ART,COMPUTER-AIDED-DESIGN},
  language     = {eng},
  number       = {2},
  pages        = {213--229},
  title        = {Evolutionary neuro-space mapping technique for modeling of nonlinear microwave devices},
  url          = {http://dx.doi.org/10.1109/TMTT.2010.2090169},
  volume       = {59},
  year         = {2011},
}

Chicago
Gorissen, Dirk, Lei Zhang, Qi Jun Zhang, and Tom Dhaene. 2011. “Evolutionary Neuro-space Mapping Technique for Modeling of Nonlinear Microwave Devices.” Ieee Transactions on Microwave Theory and Techniques 59 (2): 213–229.
APA
Gorissen, D., Zhang, L., Zhang, Q. J., & Dhaene, T. (2011). Evolutionary neuro-space mapping technique for modeling of nonlinear microwave devices. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 59(2), 213–229.
Vancouver
1.
Gorissen D, Zhang L, Zhang QJ, Dhaene T. Evolutionary neuro-space mapping technique for modeling of nonlinear microwave devices. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. 2011;59(2):213–29.
MLA
Gorissen, Dirk, Lei Zhang, Qi Jun Zhang, et al. “Evolutionary Neuro-space Mapping Technique for Modeling of Nonlinear Microwave Devices.” IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 59.2 (2011): 213–229. Print.