NDLI: An enhanced analytical Neuro-Space Mapping method for large-signal microwave device modeling

Content Provider	IEEE Xplore Digital Library
Author	Lin Zhu Kaihua Liu Zhang, Qijun Yongtao Ma Bo Peng
Copyright Year	2012
Description	Author affiliation: School of Electronics and Information Engineering, Tianjin University, China 300072 (Lin Zhu; Kaihua Liu; Zhang, Qijun; Yongtao Ma; Bo Peng)
Abstract	In this paper, an advanced Neuro-Space Mapping (SM) modeling technique for nonlinear device modeling is proposed. 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. The novelty of our work is to introduce a Neuro-SM model combining separate mappings for voltage and current and to derive analytical mapping representation to train the mapping neural networks to learn DC, small and large-signal data. Application examples on modeling MESFET devices and the use of the new model in DC, combined DC,S-parameter and Harmonic balance (HB) simulation demonstrate that our analytical Neuro-SM model matches more closely with the device data than that by the previous Neuro-SM method for modeling large-signal microwave devices.
Starting Page	1
Ending Page	3
File Size	810624
Page Count	3
File Format	PDF
ISBN	9781467310857
ISSN	0149645X
e-ISBN	9781467310888
e-ISBN	9781467310864
DOI	10.1109/MWSYM.2012.6259712
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-17
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data models Analytical models Mathematical model Training Artificial neural networks Integrated circuit modeling Scattering parameters training method Neuro-SM neural networks
Content Type	Text
Resource Type	Article
Subject	Condensed Matter Physics Electrical and Electronic Engineering Radiation

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