A Time Delay Neural Network Based Technique for Nonlinear Microwave Device Modeling

Wenyuan Liu; Lin Zhu; Feng Feng; Wei Zhang; Qi-Jun Zhang; Qian Lin; Gaohua Liu

doi:10.3390/mi11090831

A Time Delay Neural Network Based Technique for Nonlinear Microwave Device Modeling

Micromachines (Basel). 2020 Aug 31;11(9):831. doi: 10.3390/mi11090831.

Authors

Wenyuan Liu¹, Lin Zhu², Feng Feng³, Wei Zhang³, Qi-Jun Zhang³, Qian Lin⁴, Gaohua Liu⁵

Affiliations

¹ School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi'an 710021, China.
² School of Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin 300384, China.
³ Department of Electronics, Carleton University, Ottawa, ON K1S 5B6, Canada.
⁴ College of Physics and Electronic Information Engineer, Qinghai University for Nationalities, Xining 810007, China.
⁵ School of Electronics and Information Engineering, Tianjin University, Tianjin 300072, China.

Abstract

This paper presents a nonlinear microwave device modeling technique that is based on time delay neural network (TDNN). The proposed technique can accurately model the nonlinear microwave devices when compared to static neural network modeling method. A new formulation is developed to allow for the proposed TDNN model to be trained with DC, small-signal, and large signal data, which can enhance the generalization of the device model. An algorithm is formulated to train the proposed TDNN model efficiently. This proposed technique is verified by GaAs metal-semiconductor-field-effect transistor (MESFET), and GaAs high-electron mobility transistor (HEMT) examples. These two examples demonstrate that the proposed TDNN is an efficient and valid approach for modeling various types of nonlinear microwave devices.

Keywords: neural networks; nonlinear device modeling; optimization methods.

Abstract

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