The Modeling of Semiconductor Circuit Elements by Using Artificial Neural Networks
Öz
In this study, the modeling of semiconductor circuit elements very frequently used in electronic circuits are carried out by using an Artificial Neural Networks (ANN). The modeling of electronic circuit elements is very important both in respect of engineering, and in respect of practical mathematics. The FNN modeling methods are especially suited for applications where physically justified analytical circuit element models lack the required accuracy. The main aim of these modeling systems is to shorten the simulation time and to examine the real physical system applications in computer environment easily by using the model elements instead of using the ones used in real applications. This for, a PNP bipolar transistor is used as the example application. The structure of the ANN which will be used for modeling of the PNP bipolar transistor is improved and trained in MATLAB toolbox. A hybrid learning algorithm consists of back-propagation and least-squares estimation is used for training the ANN network. The PNP bipolar transistor element is modeled successfully with the obtained ANN model. Results of obtained show that the ANN modeling technique can be simply used in software tools for modeling of the PNP bipolar transistor element and the other electronic circuit elements.
Anahtar Kelimeler
System modeling, Artificial neural networks, Bipolar transistor
Kaynakça
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