Artificial neural networks for temperature dependent noise modeling of microwave transistors

被引:4
作者
Marinkovic, Z. D. [1 ]
Pronic, O. R. [1 ]
Randelovic, J. B. [1 ]
Markovic, V. V. [1 ]
机构
[1] Univ Nis, Fac Elect Engn, Nish, Serbia
关键词
neural network; MESFET; HEMT; noise modeling; temperature;
D O I
10.1080/00207210701464634
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper an automated procedure for prediction of microwave transistor noise parameters versus temperature is presented. It is based on an improved Pospieszalski's noise model. In order to avoid extraction of device noise model equivalent circuit parameters (ECP) from the measured scattering and noise parameters for each operating temperature, an artificial neural network is introduced for modeling of the ECP temperature dependence. Therefore, it is necessary to acquire the measured data and extract the ECP only for several operating temperatures used for the network training. Once the network is trained and assigned to the considered noise model, the device noise parameters are easily obtained for each temperature from the operating range. It is done without changes in the network structure and without the need for time consuming and complex measurements and optimiztions.
引用
收藏
页码:759 / 767
页数:9
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