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ICTAI
2002
IEEE
14 years 14 days ago
Function Approximation Using Robust Wavelet Neural Networks
Wavelet neural networks (WNN) have recently attracted great interest, because of their advantages over radial basis function networks (RBFN) as they are universal approximators bu...
Sheng-Tun Li, Shu-Ching Chen
BMCBI
2008
130views more  BMCBI 2008»
13 years 7 months ago
Function approximation approach to the inference of reduced NGnet models of genetic networks
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Hi...
TNN
2008
119views more  TNN 2008»
13 years 7 months ago
Selecting Useful Groups of Features in a Connectionist Framework
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Debrup Chakraborty, Nikhil R. Pal
NIPS
1990
13 years 8 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro
VISUALIZATION
2005
IEEE
14 years 1 months ago
Framework for Visualizing Higher-Order Basis Functions
Techniques in numerical simulation such as the finite element method depend on basis functions for approximating the geometry and variation of the solution over discrete regions ...
William J. Schroeder, François Bertel, Math...