Concept

Helmholtz decomposition

Related publications (39)

MATHICSE Technical Report :Convergence analysis of Padé approximations for Helmholtz frequency response problems

The present work concerns the approximation of the solution map S associated to the parametric Helmholtz boundary value problem, i.e., the map which associates to each (real) wavenumber belonging to a given interval of interest the corresponding solution o ...

MATHICSE2016

Prototropic Exchange Governs T-1 and T-2 Relaxivities of a Potential MRI Contrast Agent Nanozeolite Gd-LTL with a High pH Responsiveness

Lothar Helm

Aqueous suspensions of lanthanide exchsanged zeolite LTL have been investigated by 1H, 17O NMR, and EPR relaxivity studies. Both the longitudinal and the transverse relaxivity of these Gd3+ loaded materials are strongly pH dependent and therefore, they hav ...

American Chemical Society2015

Laplacian Support Vector Analysis for Subspace Discriminative Learning

Nikolaos Arvanitopoulos Darginis

In this paper we propose a novel dimensionality reduction method that is based on successive Laplacian SVM projections in orthogonal deflated subspaces. The proposed method, called Laplacian Support Vector Analysis, produces projection vectors, which captu ...

2014

Lithium diffusive behavior in Li2MnO3 detected by muon-spin relaxation

Martin Mansson

In a paramagnetic state of Li2MnO3, i.e. at temperatures above T-N = 35 K, muon-spin relaxation (mu+SR) measurements with zero applied magnetic field (ZF) and longitudinal-field (LF) revealed the presence of a dynamic fluctuation of a nuclear magnetic fiel ...

Elsevier Science Bv2014

Variational Decomposition of Vector Fields in the Presence of Noise

Michaël Unser, Emrah Bostan, Pouya Dehghani Tafti

We present a variational framework, and an algorithm based on the alternating method of multipliers (ADMM), for the problem of decomposing a vector field into its curl- and divergence-free components (Helmholtz decomposition) in the presence of noise. We p ...

IEEE2013

Divergence-free phase contrast MRI

Matthias Seeger, Nikolaos Arvanitopoulos Darginis

In this work, we extend a separate magnitude and phase regularization framework for Phase Contrast MRI by incorporating the divergence-free condition. ...

2013

Approximate Sparsity Pattern Recovery: Information-Theoretic Lower Bounds

Michael Christoph Gastpar

Recovery of the sparsity pattern (or support) of an unknown sparse vector from a small number of noisy linear mea- surements is an important problem in compressed sensing. In this paper, the high-dimensional setting is considered. It is shown that if the m ...

Institute of Electrical and Electronics Engineers2013

Beyond Moore-Penrose: Sparse Pseudoinverse

Martin Vetterli, Mihailo Kolundzija, Ivan Dokmanic

Frequently, we use the Moore-Penrose pseudoinverse (MPP) even in cases when we do not require all of its defining properties. But if the running time and the storage size are critical, we can do better. By discarding some constraints needed for the MPP, we ...

2013

A Dual Algorithm for $ L _{ 1 } $ -Regularized Reconstruction of Vector Fields

Michaël Unser, Emrah Bostan, Pouya Dehghani Tafti

Recent advances in vector-field imaging have brought to the forefront the need for efficient denoising and reconstruction algorithms that take the physical properties of vector fields into account and can be applied to large volumes of data. With these req ...

IEEE2012

A Dual Algorithm For L1-Regularized Reconstruction Of Vector Fields

Michaël Unser, Emrah Bostan, Pouya Dehghani Tafti

Ieee2012

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