Proceedings Article10.1109/ICONIP.2002.1198218
An efficient learning algorithm for function approximation with radial basis function networks
Yen-Jen Oyang,Shien-Ching Hwang +1 more
- 18 Nov 2002
- Vol. 2, pp 1037-1042
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TL;DR: This paper proposes a novel learning algorithm for constructing function approximators with radial basis function (RBF) networks that features lower time complexity for constructing the RBF network and is able to deliver the same level of accuracy.
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Abstract: This paper proposes a novel learning algorithm for constructing function approximators with radial basis function (RBF) networks. In comparison with the existing learning algorithms, the proposed algorithm features lower time complexity for constructing the RBF network and is able to deliver the same level of accuracy. The time taken by the proposed algorithm to construct the RBF network is in the order of O(|S|), where S is the set of training samples. As far as the time complexity for predicting the function values of input vectors is concerned, the RBF network constructed with the proposed learning algorithm can complete the task in O(|T|), where T is the set of input vectors. Another important feature of the proposed learning algorithm is that the space complexity of the RBF network constructed is O(m|S|), where m is the dimension of the vector space in which the target function is defined.
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Citations
Automatic determination of synergies by radial basis function artificial neural networks for the control of a neural prosthesis
Simona Denisia Iftime,Line Lindhardt Egsgaard,Mirjana Popovic +2 more
- 12 Dec 2005
TL;DR: An automatic method for synthesizing the control for a neural prosthesis (NP) that could augment elbow flexion/extension and forearm pronation/supination in persons with hemiplegia is described.
52
Artificial neural networks design for classification of brain tumour
S. N. Deepa,B. Aruna Devi +1 more
- 01 Mar 2012
TL;DR: The results showed outperformance of RBFN algorithm when compared to BPN with classification accuracy of 85.71% which works as promising tool for classification and requires extension in brain tumour analysis.
42
Development and performance evaluation of neural network classifiers for Indian internet shoppers
TL;DR: An in depth investigation is made on the behavior of Indian consumers towards online shopping and the RBF network provides best classification performance of internet shoppers compared to those given by the FLANN, MLP and discriminant analysis based methods.
10
A study on local sensor fusion of wireless sensor networks based on the neural network
Xiao-Liang Xu,Jun-Na Qiu,Chun Chen +2 more
- 12 Jul 2008
TL;DR: The theory of the Neural Network is outlined, mainly an introduction is made to typical fusion algorithms, along with analyses and comparisons, in three Feed-Forward neural networks, BP, RBF and CMAC, respectively.
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Comparative Study of De-Noising,Segmentation, Feature Extraction,Classification Techniques for Medical Images
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