A Comparison of RBF Neural Network Training Algorithms for Inertial Sensor Based Terrain Classification

A Comparison of RBF Neural Network Training Algorithms for Inertial Sensor Based Terrain Classification

This paper introduces a comparison of training algorithms of radial basis function (RBF) neural networks for classification purposes. RBF networks provide effective solutions in many science and engineering fields. They are especially popular in the pattern classification and signal processing areas...

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Bibliographic Details
Main Authors: Erkan Beşdok, Tuba Kurban
Format: Article
Language:English
Published: MDPI AG 2009-08-01
Series:Sensors
Subjects:
radial basis neural networks
terrain classification
inertial navigation sensors
genetic algorithm
artificial bee colony algorithm
Kalman filtering
gradient descent
Online Access:http://www.mdpi.com/1424-8220/9/8/6312/

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http://www.mdpi.com/1424-8220/9/8/6312/

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