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» Complex ICA Using Nonlinear Functions
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EUSFLAT
2009
245views Fuzzy Logic» more  EUSFLAT 2009»
13 years 6 months ago
Universal Approximation of a Class of Interval Type-2 Fuzzy Neural Networks Illustrated with the Case of Non-linear Identificati
Neural Networks (NN), Type-1 Fuzzy Logic Systems (T1FLS) and Interval Type-2 Fuzzy Logic Systems (IT2FLS) are universal approximators, they can approximate any non-linear function....
Juan R. Castro, Oscar Castillo, Patricia Melin, An...
PAMI
2006
142views more  PAMI 2006»
13 years 8 months ago
Fingerprint Warping Using Ridge Curve Correspondences
The performance of a fingerprint matching system is affected by the nonlinear deformation introduced in the fingerprint impression during image acquisition. This nonlinear deformat...
Arun Ross, Sarat C. Dass, Anil K. Jain
GECCO
2008
Springer
174views Optimization» more  GECCO 2008»
13 years 9 months ago
Mask functions for the symbolic modeling of epistasis using genetic programming
The study of common, complex multifactorial diseases in genetic epidemiology is complicated by nonlinearity in the genotype-to-phenotype mapping relationship that is due, in part,...
Ryan J. Urbanowicz, Nate Barney, Bill C. White, Ja...
POPL
2009
ACM
14 years 9 months ago
SPEED: precise and efficient static estimation of program computational complexity
This paper describes an inter-procedural technique for computing symbolic bounds on the number of statements a procedure executes in terms of its scalar inputs and user-defined qu...
Sumit Gulwani, Krishna K. Mehra, Trishul M. Chilim...
NIPS
2003
13 years 10 months ago
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...