|
Twitter
|
Facebook
|
Google+
|
VKontakte
|
LinkedIn
|
Viadeo
|
English
|
Français
|
Español
|
العربية
|
 
International Journal of Innovation and Applied Studies
ISSN: 2028-9324     CODEN: IJIABO     OCLC Number: 828807274     ZDB-ID: 2703985-7
 
 
Friday 15 November 2019

About IJIAS

News

Submission

Downloads

Archives

Custom Search

Contact

Connect with IJIAS

  Call for Papers - November 2019     |     Now IJIAS is indexed in EBSCO, ResearchGate, ProQuest, Chemical Abstracts Service, Index Copernicus, IET Inspec Direct, Ulrichs Web, Google Scholar, CAS Abstracts, J-Gate, UDL Library, CiteSeerX, WorldCat, Scirus, Research Bible and getCited, etc.  
 
 
 

Modeling the Drain Current of a PHEMT using the Artificial Neural Networks and a Taylor Series Expansion


Volume 10, Issue 1, January 2015, Pages 132–137

 Modeling the Drain Current of a PHEMT using the Artificial Neural Networks  and a Taylor Series Expansion

Taj-eddin Elhamadi1, Mohamed Boussouis2, and Naima Amar Touhami3

1 Electronic and Instrumentation laboratory, Faculty of Science, Abdmalak Essaadi University, Tetouan, Morocco
2 Electronic and Instrumentation laboratory, Faculty of Science, Abdmalak Essaadi University, Tetouan, Morocco
3 Electronic and Instrumentation laboratory, Faculty of Science, Abdmalak Essaadi University, Tetouan, Morocco

Original language: English

Received 26 October 2014

Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


Artificial neural networks (ANNs) have recently been introduced in the microwave area as a fast and flexible vehicle to microwave modeling, simulation and optimization. The models are fast and can represent EM/physics behaviors it learnt which otherwise are computationally expensive. In this paper a neural network model is developed for a Pseudomorphic High Electron Mobility Transistor PHEMT (ED02AH-6x30), a transistor of 6 gate fingers, each with a width of 30

Author Keywords: Neural networks, multi-layer perceptron, back propagation algorithm, PHEMT, Taylor series expansion.


How to Cite this Article


Taj-eddin Elhamadi, Mohamed Boussouis, and Naima Amar Touhami, “Modeling the Drain Current of a PHEMT using the Artificial Neural Networks and a Taylor Series Expansion,” International Journal of Innovation and Applied Studies, vol. 10, no. 1, pp. 132–137, January 2015.