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» Modeling Nonlinear Time Series Using Improved Least Squares ...
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PAMI
2012
11 years 10 months ago
A Least-Squares Framework for Component Analysis
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
Fernando De la Torre
ICML
2006
IEEE
14 years 8 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
ICASSP
2009
IEEE
13 years 5 months ago
Adaptive predistortion of nonlinear Volterra systems using Spectral Magnitude Matching
Digital compensation of nonlinear systems is an important topic in many practical applications. This paper considers the problem of predistortion of nonlinear systems described us...
Emad Abd-Elrady, Li Gan, Gernot Kubin
DMIN
2008
241views Data Mining» more  DMIN 2008»
13 years 9 months ago
Leakage Detection by Adaptive Process Modeling
Abstract-- In this paper, we propose an adaptive linear approach for time series modeling and steam line leakage detection. Weighted recursive least squares (WRLS) method is used f...
Jaakko Talonen, Miki Sirola, Jukka Parviainen
IWANN
2009
Springer
14 years 2 months ago
Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints
This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...