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» Functional radial basis function networks
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NPL
2002
145views more  NPL 2002»
13 years 7 months ago
Hybrid Feedforward Neural Networks for Solving Classification Problems
A novel multistage feedforward network is proposed for efficient solving of difficult classification tasks. The standard Radial Basis Functions (RBF) architecture is modified in or...
Iulian B. Ciocoiu
CGF
2006
120views more  CGF 2006»
13 years 7 months ago
Enhancing the Interactive Visualization of Procedurally Encoded Multifield Data with Ellipsoidal Basis Functions
Functional approximation of scattered data is a popular technique for compactly representing various types of datasets in computer graphics, including surface, volume, and vector ...
Yun Jang, Ralf P. Botchen, Andreas Lauser, David S...
IJCNN
2000
IEEE
14 years 3 days ago
Support Vector Machine for Regression and Applications to Financial Forecasting
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...
Theodore B. Trafalis, Huseyin Ince
ESANN
2008
13 years 9 months ago
Selection of important input variables for RBF network using partial derivatives
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
Jarkko Tikka, Jaakko Hollmén
IWANN
2001
Springer
14 years 5 days ago
Evolving RBF Neural Networks
This paper is focused on determining the parameters of radial basis function neural networks (number of neurons, and their respective centers and radii) automatically. While this ...
Víctor Manuel Rivas Santos, Pedro A. Castil...