A review of neural network based techniques for nonlinear microwave device modeling

Author(s):  
Wenyuan Liu ◽  
Weicong Na ◽  
Lin Zhu ◽  
Qi-Jun Zhang
Micromachines ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 831
Author(s):  
Wenyuan Liu ◽  
Lin Zhu ◽  
Feng Feng ◽  
Wei Zhang ◽  
Qi-Jun Zhang ◽  
...  

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.


Author(s):  
Lin Zhu ◽  
Jian Zhao ◽  
Zhuo Li ◽  
Wenyuan Liu ◽  
Lei Pan ◽  
...  

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