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Sensitivity driven artificial neural network correction models for RF/microwave devices
Author(s) -
Devabhaktuni Vijay,
Mareddy Lakshman,
Vemuru Srinivas,
Cheruvu Vani,
Goykhman Yuriy,
Ozdemir Tayfun
Publication year - 2012
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.20581
Subject(s) - sensitivity (control systems) , artificial neural network , microwave , microstrip , electronic engineering , radio frequency , computer science , spiral (railway) , engineering , artificial intelligence , telecommunications , mechanical engineering
In this article, we propose a sensitivity based correction model that improves the accuracy of the neural model keeping the structure of artificial neural network (ANN) simple. The proposed approach is applied to the modeling of RF transistors, spiral inductors, and microstrip antennas. Results are compared with conventional ANN and a recent technique referred to as correction model that is assisted by the regula‐falsi method. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.