Analysis and validation of neural network approach for extraction of small-signal model parameters of microwave transistors

Comparative Analysis of Different Cad Methods for Extraction of the Hemt Noise Wave Model Parameters

“…The field of electrical engineering has proved to be a very suitable for the ANN applications [26][27][28][29][30][31][32][33][34][35]. By learning the dependence between two datasets, ANNs have the capability to approximate any nonlinear function, whereby the knowledge about the physical characteristics of the problem to be modeled is not needed [36].…”

Artifical neural networks in RF MEMS switch modelling

“…The most important feature of ANNs is their generalization ability, i.e., the ability to generate the correct response even for the input parameter values not included in the training set. The generalization ability has qualified ANNs to be used as an efficient tool for modelling in the field of RF and microwaves [26][27][28][29][30][31][32][33][34][35][36]. As examples, ANNs could be used as an alternative to time-consuming electromagnetic simulations [26][27][28]30] or an alternative to the conventional modelling of microwave devices [25,27,30,32,35,36].…”

Novel neural approach for parameter extraction of microwave transistor noise models

“…), having in mind that the device characteristics depend on the operating conditions, it is necessary to repeat extraction procedures for each new combination of operating conditions, which can be quite time consuming. Therefore, a research on the development of alternative extraction procedures has been performed, leading also to efficient procedures based on artificial neural networks (ANNs) [14][15][16][17][18][19][20]. One approach is based on ANNs trained to learn dependence of ECPs on operating conditions [14][15][16][17].…”

“…One approach is based on ANNs trained to learn dependence of ECPs on operating conditions [14][15][16][17]. In an alternative approach, ANNs are used for determination of the ECPs directly from the measured transistor characteristics [18,19]. These two approaches were compared in [20], and some of the details are presented in this paper as well.…”