Concept

Kernel principal component analysis

Related publications (153)

Insight gained from Principal Component Analysis in the analysis of river morphodynamics and associated sediment fluxes.

Christophe Ancey, Joris Heyman, Blaise Etienne Marceau Dhont

Bedload transport fluxes are known to widely fluctuate in both time and space (Ma et al., 2014). The typical scales of fluctuations are broad and often overlap: from random particle motions at the grain scale to large bed morphologies evolving at the river ...

2017

High-Order Accurate Adaptive Kernel Compression Time-Stepping Schemes for Fractional Differential Equations

Jan Sickmann Hesthaven, Daniel Henri Baffet

High-order adaptive methods for fractional differential equations are proposed. The methods rely on a kernel reduction method for the approximation and localization of the history term. To avoid complications typical to multistep methods, we focus our stud ...

Springer Verlag2017

Fast Robust PCA on Graphs

Pierre Vandergheynst, Gilles Puy, Nathanaël Perraudin, Nauman Shahid, Vasilis Kalofolias

Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Efficient Statistical Parameter Selection for Nonlinear Modeling of Process/Performance Variation

Giovanni De Micheli, Pierre-Emmanuel Julien Marc Gaillardon, Hassan Ghasemzadeh Mohammadi

With the growing number of process variation sources in deeply nano-scaled technologies, parameterized device and circuit modeling is becoming very important for chip design and verification. However, the high dimensionality of parameter space, for process ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Eigenmaps Of Dynamic Functional Connectivity: Voxel-Level Dominant Patterns Through Eigenvector Centrality

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti

Dynamic functional connectivity (dFC) based on resting-state functional magnetic resonance imaging (fMRI) explores the ongoing temporal configuration of brain networks. To reduce the large dimensionality of the data, conventional dFC analysis usually fores ...

IEEE2016

Global Sensitivity Analysis of Transient Code Output Applied to a Reflood Experiment Model using the TRACE Code

Andreas Pautz, Damar Canggih Wicaksono, Omar Zerkak

Appropriate model assessment requires proper understanding of the impact of variations of model parameters and their interactions on results. However, in many thermal-hydraulic (TH) simulations, the code often predicts time-dependent output where the impac ...

American Nuclear Society2016

Ballistocardiogram artifact correction taking into account physiological signal preservation in simultaneous EEG-fMRI

Wietske Van der Zwaag, João Pedro Forjaco Jorge, Patricia Figueiredo, Ana Francisca Leal Silva Soares

The ballistocardiogram (BCG) artifact is currently one of the most challenging in the EEG acquired concurrently with fMRI, with correction invariably yielding residual artifacts and/or deterioration of the physiological signals of interest. In this paper, ...

Elsevier2016

Spatial interpolation of experimental raindrop size distribution spectra

Alexis Berne, Timothy Hugh Raupach

We present a new approach for spatial interpolation of experimental raindrop size distribution (DSD) spectra. The DSD is fundamental to the study and understanding of precipitation and its monitoring and modelling. It is measured insitu using disdrometers ...

Wiley-Blackwell2016

Intersegmental coordination elicited by unexpected multidirectional slipping-like perturbations resembles that adopted during steady locomotion

Silvestro Micera

This study aimed at testing the hypothesis that reactive biomechanical responses elicited by unexpected slipping-like perturbations delivered during steady walking are characterized by an intersegmental coordination strategy resembling that adopted during ...

Amer Physiological Soc2016

Steerable PCA for Rotation-Invariant Image Recognition

Michaël Unser, Cédric René Jean Vonesch, Frédéric Stauber

In this paper, we propose a continuous-domain version of principal-component analysis, with the constraint that the underlying family of templates appears at arbitrary orientations. We show that the corresponding principal components are steerable. Our met ...

SIAM2015

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