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A simple and efficient approach to train artificial neural networks using a genetic algorithm to calculate the resonant frequency of an RMA on thick substrate

✍ Scribed by Bonomali Khuntia; Shyam S. Pattnaik; Dhruba C. Panda; Dipak K. Neog; S. Devi; Malay Dutta

Publisher: John Wiley and Sons
Year: 2004
Tongue: English
Weight: 249 KB
Volume: 41
Category: Article
ISSN: 0895-2477
DOI: 10.1002/mop.20126

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✦ Synopsis

Abstract

Both genetic algorithms (GAs) and artificial neural networks (ANNs) have been used in the field of computational electromagnetics as the most powerful optimizing tools. In this paper, a simple and efficient method is presented to handle the problem of competing convention while training an ANN by using a GA. This technique is applied to calculate the resonant frequency of a thick‐substrate rectangular microstrip antenna (RMA). The training time is less than that of a normal feed‐forward backpropagation algorithm. The measured results are in very good agreement with experimental results. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 41: 313–315, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20126

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