Modelling of active microwave transistors using artificial neural networks

Abstract

Signal and noise behaviours of microwave transistors are modeled through the neural network approach for the whole operating ranges including frequency bias and configuration types. Here, the device is modeled by a black box whose small-signal and noise parameters are evaluated through various neural network methods, based upon the fitting of both of these parameters for multiple bias and configuration. Previous results are improved with a conic section function neural network method presented in this work.

Keywords

Artificial neural network SIGNAL (programming language) Microwave Computer science Noise (video) Electronic engineering Conic section Transistor Artificial intelligence Engineering Electrical engineering Voltage Telecommunications Mathematics

Subject Areas

Photonic and Optical Devices ·Electrical and Electronic Engineering ·Physical Sciences

Semiconductor Lasers and Optical Devices ·Electrical and Electronic Engineering ·Physical Sciences

Radio Frequency Integrated Circuit Design ·Electrical and Electronic Engineering ·Physical Sciences

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Modelling of active microwave transistors using artificial neural networks

Abstract

Keywords

Subject Areas

Citations by Year

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References (2)

Cited by (9)

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