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» Nonlinear functional regression: a functional RKHS approach
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ML
2007
ACM
106views Machine Learning» more  ML 2007»
14 years 9 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
DATE
2005
IEEE
100views Hardware» more  DATE 2005»
15 years 3 months ago
Modeling the Non-Linear Behavior of Library Cells for an Accurate Static Noise Analysis
In signal integrity analysis, the joint effect of propagated noise through library cells, and of the noise injected on a quiet net by neighboring switching nets through coupling c...
Cristiano Forzan, Davide Pandini
AUTOMATICA
2005
112views more  AUTOMATICA 2005»
14 years 9 months ago
Optimal controller tuning for nonlinear processes
: This work proposes a systematic methodology for the optimal selection of controller parameters, in the sense of minimizing a performance index which is a quadratic function of th...
Nikolaos Kazantzis, Costas Kravaris, Costas Tseron...
ISBI
2008
IEEE
15 years 10 months ago
Inferring brain dynamics using granger causality on fMRI data
Here we present a scalable method to compute the structure of causal links over large scale dynamical systems that achieves high efficiency in discovering actual functional connec...
Guillermo A. Cecchi, Rahul Garg, A. Ravishankar Ra...
HYBRID
2010
Springer
15 years 4 months ago
Accurate hybridization of nonlinear systems
This paper is concerned with reachable set computation for non-linear systems using hybridization. The essence of hybridization is to approximate a non-linear vector field by a s...
Thao Dang, Oded Maler, Romain Testylier