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Radial Basis Functions Networks
2002The solution of complex mapping problems with artificial neural networks normally demands the use of a multi-layer network structure. This multi-layer topology process data into consecutive steps in each one of the layers. Radial Basis Functions networks are a particular neural network structure that uses radial functions in the intermediate, or hidden,
A. Braga +4 more
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Radial-Basis Function Networks
2000This chapter deals with a special class of artificial neural networks (ANNs) called radial-basis function (RBF) networks. These networks derive their structure and interpretation from the theory of interpolation in multidimensional spaces, and have a mathematical foundation imbedded in regularization theory for solving ill-conditioned problems.
Rao S. Govindaraju, Bin Zhang
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Multiscale Radial Basis Functions
2017Radial basis functions (RBFs) are a popular meshfree discretisation method for constructing high-order approximation spaces. They are used in various areas comprising, for example, scattered data approximation, computer graphics, machine learning, aeroelasticity and the geosciences.The approximation space is usually formed using the shifts of a fixed ...
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
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Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma
Ca-A Cancer Journal for Clinicians, 2020Aaron J Grossberg +2 more
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Oral complications of cancer and cancer therapy
Ca-A Cancer Journal for Clinicians, 2012Joel B Epstein +2 more
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