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Nonideal sampling and regularized interpolation of noisy data

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Linear Interpolation Of Biomedical Images Using A Data-Adaptive Kernel

Michaël Unser, John Paul Ward, Aurélien Bourquard, Hagay Kirshner

In this work, we propose a continuous-domain stochastic model that can be applied to image data. This model is autoregressive, and accounts for Gaussian-type as well as for non-Gaussian-type innovations. In order to estimate the corresponding parameters fr ...

IEEE2013

Sparse Distributed Learning Based on Diffusion Adaptation

Ali H. Sayed

This article proposes diffusion LMS strategies for distributed estimation over adaptive networks that are able to exploit sparsity in the underlying system model. The approach relies on convex regularization, common in compressive sensing, to enhance the d ...

IEEE2013

On L2-Regularization for Virtual Reference Feedback Tuning

Alireza Karimi

The Virtual Reference Feedback Tuning (VRFT) approach is a design method that allow optimal feedback control laws to be derived from input-output (I/O) data only, without need of a model of the process. A drawback of this methods is that, in its standard f ...

2013

Manifold Sparse Beamforming

Volkan Cevher, Afsaneh Asaei, Baran Gözcü

We consider the minimum variance distortionless response (MVDR) beamforming problems where the array covariance matrix is rank deficient. The conventional approach handles such rank-deficiencies via diagonal loading on the covariance matrix. In this settin ...

2013

Manifold Sparse Beamforming

Volkan Cevher, Afsaneh Asaei, Baran Gözcü

IEEE2013

An optimal error nonlinearity for robust adaptation against impulsive noise

Ali H. Sayed, Ali Zoubir

The least-mean squares algorithm is non-robust against impulsive noise. Incorporating an error nonlinearity into the update equation is one useful way to mitigate the effects of impulsive noise. This work develops an adaptive structure that parametrically ...

IEEE2013

The dilaton Wess-Zumino action in higher dimensions

Boaz Keren Zur, Florent Baume

We present a general formula for the Wess-Zumino action associated with the Weyl anomaly, given in a curved background for any even number of dimensions. The result is obtained by considering a finite Weyl transformation of counterterms in dimensional regu ...

Springer2013

A Sequential Topic Model for Mining Recurrent Activities from Long Term Video Logs

Jean-Marc Odobez, Rémi Emonet, Jagannadan Varadarajan

This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns called motifs from documents given as word×time count matrices (e.g., videos). In this model, documents are represented as a mixture of sequenti ...

Springer2013

On Sparsity Averaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

Recent developments in [1] and [2] introduced a novel regularization method for compressive imaging in the con- text of compressed sensing with coherent redundant dictionaries. The approach relies on the observation that natural images exhibit strong avera ...

2013

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