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Fast Projection Onto Convex Smooth Constraints

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Approximate dynamic programming via sum of squares programming

Maryam Kamgarpour, Tyler Summers

We describe an approximate dynamic programming method for stochastic control problems on infinite state and input spaces. The optimal value function is approximated by a linear combination of basis functions with coefficients as decision variables. By rela ...

2013

Stochastic Exploration of Ambiguities for Non-Rigid Shape Recovery

Pascal Fua

Recovering the 3D shape of deformable surfaces from single images is known to be a highly ambiguous problem because many different shapes may have very similar projections. This is commonly addressed by restricting the set of possible shapes to linear comb ...

Institute of Electrical and Electronics Engineers2013

Quotient-method Algorithms for Input-affine Single-input Nonlinear Systems

Willson Sudarsandhari Shibani

Many real-world systems are intrinsically nonlinear. This thesis proposes various algorithms for designing control laws for input-affine single-input nonlinear systems. These algorithms, which are based on the concept of quotients used in nonlinear control ...

EPFL2012

Comparison of measured and simulated fast ion velocity distributions in the TEXTOR tokamak

Mattia Albergante, Otto Asunta

Here we demonstrate a comprehensive comparison of collective Thomson scattering (CTS) measurements with steady-state Monte Carlo simulations performed with the ASCOT and VENUS codes. The measurements were taken at a location on the magnetic axis as well as ...

2011

Sparse Approximations Of Protein Structure From Noisy Random Projections

Victor Panaretos, Kjell Konis

Single-particle electron microscopy is a modern technique that biophysicists employ to learn the structure of proteins. It yields data that consist of noisy random projections of the protein structure in random directions, with the added complication that ...

2011

Compressed sensing for wide-field radio interferometric imaging

Yves Wiaux, Jason Douglas McEwen

For the next generation of radio interferometric telescopes it is of paramount importance to incorporate wide field-of-view (WFOV) considerations in interferometric imaging, otherwise the fidelity of reconstructed images will suffer greatly. We extend comp ...

Wiley-Blackwell2011

Local Multilayer Analytic Sensing For Eeg Source Localization: Performance Bounds And Experimental Results

Dimitri Nestor Alice Van De Ville, Thierry Blu, Clotaire Michel, Djano Kandaswamy

Analytic sensing is a new mathematical framework to estimate the parameters of a multi-dipole source model from boundary measurements. The method deploys two working principles. First, the sensing principle relates the boundary measurements to the volumetr ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Wavelet transform on manifolds: old and new approaches

Pierre Vandergheynst

Given a two-dimensional smooth manifold M and a bijective pro jection p from M on a ﬁxed plane (or a subset of that plane), we explore systematically how a wavelet transform (WT) on M may be generated from a plane WT by the inverse projection. Examples whe ...

Elsevier2010

On Random Tomography with Unobservable Projection Angles

Victor Panaretos

We formulate and investigate a statistical inverse problem of a random tomographic nature, where a probability density function on

\mathbb{R}^3

is to be recovered from observation of finitely many of its two-dimensional projections in random and unobserv ...

Institute of Mathematical Statistics2009

A compressive beamforming method

Volkan Cevher

Compressive Sensing (CS) is an emerging area which uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compressible signals. This paper considers the direction-of-arrival (DOA) estimation ...

2008

On Random Tomography with Unobservable Projection Angles

Victor Panaretos

We formulate and investigate a statistical inverse problem of a random tomographic nature, where a probability density function on

\mathbb{R}^3

is to be recovered from observation of finitely many of its two-dimensional projections in random and unobserv ...

Institute of Mathematical Statistics2009