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

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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.
Keywords
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

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Citation

Please use this url to cite or link to this publication:

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.
@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},
}

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