[PDF] Top 20 Compressed sensing with unknown sensor permutation

... the sensing process: the dictionary is known up to a permu- tation of its ...setup with a large number of sensors – ...the sensor permutation problem 1 ... Voir le document complet

... remote sensing images is the pansharpening, which generally consists of fusing a high spatial resolution panchro- matic (PAN) image and a low spatial resolution multispectral (MS) ... Voir le document complet

... structure with the potential of being applied in situ (laser vibrometer, optical sensor, etc) ...optimal sensor placement and optimal frequency sampling is a common problem encountered in many ... Voir le document complet

... model. With each model, there are different assumptions made of the data, and certain models are more applicable for specific data (for example, one model may account for local variation better than ...to ... Voir le document complet

... These notions are unfortunately expected to be difficult to compute because of the following result [36]. Theorem 5.3 (Vardy). It is NP-hard to compute the girth of a vector matroid over a finite field of two elements, ... Voir le document complet

... remote sensing images is the pansharpening, which generally consists of fusing a high spatial resolution panchro- matic (PAN) image and a low spatial resolution multispectral (MS) ... Voir le document complet

... In this paper, we modeled secretory events that result in cortisol time series, and proposed a coordinate descent approach to estimate the model parameters and recover the sparse time- varying secretory input. ... Voir le document complet

... Dealing with such a volume of data has important consequences on embedded resources, which require more memory, more computing capacity and therefore more powerful electrical ...then compressed by some ... Voir le document complet

... dictionary learning, which are known to be highly non-convex and riddled with local minima. In the considered context, we show that in fact this formulation can be exactly expressed as a convex opti- mization ... Voir le document complet

... 279848 sensing matrix was ...the sensing matrix, a parameter taking different values from realization to realization of the sensing matrix and whose evaluation represents a combinatorial complexity ... Voir le document complet

... latter with a high degree of ...generalist with a long track record of reviews to a young specialist with deep exper- tise in the specific area but possibly strong subjective judgments that are ... Voir le document complet

... L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignemen[r] ... Voir le document complet

... estimator with sub-optimal threshold (SOT) [12] (the estimated number of channel taps ˆ S is set to be the channel sparsity S) and 25% of pilots in the overall considered E b / N 0 , how- ever, the spectral ... Voir le document complet

... small. The slight gain can be explained by the fact that g- and s-OSCAR versions mix up different oriented details or resolution information together. We observed that coefficient- wise regularization performs slightly ... Voir le document complet

... 1 Introduction The efficient acquisition of sparse signals has been made possible by Compressed Sensing (CS) [3]. This technique has now many applications: in medical imaging [4, 5] for instance, where ... Voir le document complet

... 3 Introduction Recent advances in the static magnetic field strength of magnetic resonance scanners and in the radio-frequency (RF) detector designs has allowed magnetic resonance microscopy (MRM) to reach spatial ... Voir le document complet

... In this work we propose a new way of accelerating MR image reconstruction in the context of CS-accelerated acquisitions. Instead of performing offline image reconstruction by minimizing a sparsity promoting regularized ... Voir le document complet

... for sensor data processing is not immediate. However, opportunistic sensing can be ...chair, with the sensor embedded into the headrest of the massage ...of sensor data, thereby ... Voir le document complet

... πe 6 2 −2R . (12) Sketch of proof. We use a novel result about the expected value of a matrix following a generalized inverse Wishart distribution [13, Theorem 2.1]. This result can be applied to the distortion of the ... Voir le document complet

... Index Terms— Instance optimality, null space property, restricted isometry property, union-of-subspaces 1. INTRODUCTION Traditional results in sparse recovery relate certain properties of a dimensionality-reducing matrix ... Voir le document complet