Real-time system identification of an unmanned
quadcopter system using fully tuned radial basis
function neural networks

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Real-time system identification of an unmanned quadcopter system using fully tuned radial basis function neural networks

In this paper, we present the performance analysis of a fully tuned neural network trained with the extended minimal resource allocating network (EMRAN) algorithm for real-time identification of a quadcopter. Radial basis function network (RBF) based on system identification can be utilised as...

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Bibliographic Details
Main Authors:	Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Yaakub, Mohd Fauzi, Mohd Anwar, Mohd Shazlan
Format:	Article
Language:	English
Published:	Inder Science 2021
Subjects:	TL Motor vehicles. Aeronautics. Astronautics
Online Access:	http://eprints.uthm.edu.my/6616/ http://eprints.uthm.edu.my/6616/1/J13840_86bfec0ace2c4bbe3417b0d967ad1cc3.pdf

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