Litcius/Paper detail

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

2020Micromachines30 citationsDOIOpen Access PDF

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.

Topics & Concepts

MESFETArtificial neural networkComputer scienceNonlinear systemMicrowaveHigh-electron-mobility transistorElectronic engineeringGeneralizationSIGNAL (programming language)TransistorEngineeringArtificial intelligenceElectrical engineeringField-effect transistorTelecommunicationsPhysicsMathematical analysisProgramming languageVoltageMathematicsQuantum mechanicsMicrowave Engineering and WaveguidesRadio Frequency Integrated Circuit DesignPhotonic and Optical Devices