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AMCS
2008
146views Mathematics» more  AMCS 2008»
15 years 6 months ago
Fault Detection and Isolation with Robust Principal Component Analysis
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
Yvon Tharrault, Gilles Mourot, José Ragot, ...
AUTOMATICA
2006
76views more  AUTOMATICA 2006»
15 years 5 months ago
Nonlinear robust performance analysis using complex-step gradient approximation
In this paper, the complex-step method is applied in the setting of numerical optimisation problems involving dynamical systems modelled as nonlinear differential equations. The m...
Jongrae Kim, Declan G. Bates, Ian Postlethwaite
ICA
2007
Springer
15 years 12 months ago
Robust Independent Component Analysis Using Quadratic Negentropy
We present a robust algorithm for independent component analysis that uses the sum of marginal quadratic negentropies as a dependence measure. It can handle arbitrary source densit...
Jaehyung Lee, Taesu Kim, Soo-Young Lee
PRL
2010
310views more  PRL 2010»
15 years 4 months ago
A Lagrangian Half-Quadratic approach to robust estimation and its applications to road scene analysis
We consider the problem of fitting linearly parameterized models, that arises in many computer vision problems such as road scene analysis. Data extracted from images usually cont...
Jean-Philippe Tarel, Pierre Charbonnier
157
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AUTOMATICA
2008
167views more  AUTOMATICA 2008»
15 years 6 months ago
Stability and robustness analysis of nonlinear systems via contraction metrics and SOS programming
A wide variety of stability and performance questions about linear dynamical systems can be reformulated as convex optimization problems involving linear matrix inequalities (LMIs...
Erin M. Aylward, Pablo A. Parrilo, Jean-Jacques E....