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» Normalized Gaussian Radial Basis Function networks
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ESANN
2007
14 years 11 months ago
Controlling complexity of RBF networks by similarity
Abstract. Using radial basis function networks for function approximation tasks suffers from unavailable knowledge about an adequate network size. In this work, a measuring techni...
Ulrich Rückert, Ralf Eickhoff
ESANN
2001
14 years 10 months ago
Constructive density estimation network based on several different separable transfer functions
Networks estimating probability density are usually based on radial basis function of the same type. Feature Space Mapping constructive network based on separable functions, optimi...
Wlodzislaw Duch, Rafal Adamczak, Geerd H. F. Dierc...
COLT
1994
Springer
15 years 1 months ago
Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes
We examine the relationship between the VCdimension and the number of parameters of a smoothly parametrized function class. We show that the VC-dimension of such a function class ...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
JCP
2008
138views more  JCP 2008»
14 years 9 months ago
Radar Signal Detection In Non-Gaussian Noise Using RBF Neural Network
In this paper, we suggest a neural network signal detector using radial basis function (RBF) network. We employ this RBF Neural detector to detect the presence or absence of a know...
Dilip Gopichand Khairnar, S. N. Merchant, Uday B. ...
ICASSP
2011
IEEE
14 years 1 months ago
Arccosine kernels: Acoustic modeling with infinite neural networks
Neural networks are a useful alternative to Gaussian mixture models for acoustic modeling; however, training multilayer networks involves a difficult, nonconvex optimization that...
Chih-Chieh Cheng, Brian Kingsbury