Matching Pursuit with Block Incoherent Dictionaries

There has been an intense activity recently in the field of sparse approximations with redundant dictionaries, largely motivated by the practical performances of algorithms such as Matching Pursuit and Basis Pursuit. However, most of the theoretical results obtained so far are valid only for the restricted class of incoherent dictionaries. This paper investigates a new class of overcomplete dictionaries, called block incoherent dictionaries, where coherence can be arbitrarily big. We show that a simple greedy algorithm can correctly identify stable subdictionaries (called blocks) and demonstrate how one can use the extra coherence freedom for approximation purposes

Image compression using an edge adapted redundant dictionary and wavelets

Low bit rate image coding is an important problem regarding applications such as storage on low memory devices or streaming data on the internet. The state of the art in image compression is to use 2-D wavelets. The advantages of wavelet bases lie in their multiscale nature and in their ability to sparsely represent functions that are piecewise smooth. Their main problem on the other hand, is that in 2-D wavelets are not able to deal with the natural geometry of images, i.e they cannot sparsely represent objects that are smooth away from regular submanifolds. In this paper we propose an approach based on building a sparse representation of the edge part of images in a redundant geometrically inspired library of functions, followed by suitable coding techniques. Best N-terms non-linear approximations in general dictionaries is, in most cases, a NP-hard problem and sub-optimal approaches have to be followed. In this work we use a greedy strategy, also known as Matching Pursuit to compute the expansion. The residual, that we suppose to be the smooth and texture part, is then coded using wavelets. A rate distortion optimization procedure choses the number of functions from the redundant dictionary and the wavelet basis

Very low bit rate image coding using redundant dictionaries

Very low bit rate image coding is an important problem regarding applications such as storage on low memory devices or streaming data on the internet. The state of the art in image compression is to use 2-D wavelets. The advantages of wavelet bases lie in their multiscale nature and in their ability to sparsely represent functions that are piecewise smooth. Their main problem on the other hand, is that in 2-D wavelets are not able to deal with the natural geometry of images, i.e they cannot sparsely represent objects that are smooth away from regular submanifolds. In this paper we propose an approach based on building a sparse representation of images in a redundant geometrically inspired library of functions, followed by suitable coding techniques. Best N-term non- linear approximations in general dictionaries is, in most cases, a NP-hard problem and sub-optimal approaches have to be followed. In this work we use a greedy strategy, also known as Matching Pursuit to compute the expansion. Finally the last step in our algorithm is an enhancement layer that encodes the residual image: in our simulation we have used a genuine embedded wavelet codec

Hybrid video coding using bi-dimensional matching pursuit

In this report we propose a new coding scheme based on the Matching Pursuit algorithm and exploiting some of the new features introduced by H.264 for motion estimation. Main points of this work are the design of a redundant dictionary suitable for coding displaced frame dierences, the use of fast techniques for atom selection, which work in the Fourier domain and exploit the spatial localization of the atoms, the adaptive coding scheme aimed at optimizing the resouce allocation for transmitting the atom parameters and the Rate-Distortion optimization

Hybrid Video Coding based on Bidimensional Matching Pursuit

Hybrid video coding combines together two stages: first, motion estimation and compensation predict each frame from the neighboring frames, then the prediction error is coded, reducing the correlation in the spatial domain. In this work, we focus on the latter stage, presenting a scheme that profits from some of the features introduced by the standard H.264/AVC for motion estimation and replaces the transform in the spatial domain. The prediction error is so coded using the matching pursuit algorithm which decomposes the signal over an appositely designed bidimensional, anisotropic, redundant dictionary. Comparisons are made among the proposed technique, H.264, and a DCT-based coding scheme. Moreover, we introduce fast techniques for atom selection, which exploit the spatial localization of the atoms. An adaptive coding scheme aimed at optimizing the resource allocation is also presented, together with a rate-distortion study for the matching pursuit algorithm. Results show that the proposed scheme outperforms the standard DCT, especially at very low bit rates

Cardiac and vascular phenotypes in the apolipoprotein E-deficient mouse

Cardiovascular death is frequently associated with atherosclerosis, a chronic multifactorial disease and a leading cause of death worldwide. Genetically engineered mouse models have proven useful for the study of the mechanisms underlying cardiovascular diseases. The apolipoprotein E-deficient mouse has been the most widely used animal model of atherosclerosis because it rapidly develops severe hypercholesterolemia and spontaneous atherosclerotic lesions similar to those observed in humans. In this review, we provide an overview of the cardiac and vascular phenotypes and discuss the interplay among nitric oxide, reactive oxygen species, aging and diet in the impairment of cardiovascular function in this mouse model

Acquisition of digital evidence in android smartphones

From an expert\u27s perspective, an Android phone is a large data repository that can be stored either locally or remotely. Besides, its platform allows analysts to acquire device data, collecting information about its owner and facts that are under investigation. This way, by exploring and cross referencing that rich data source, one can get information related to unlawful acts and its perpetrator. There are widespread and well documented approaches to forensic examining mobile devices and computers. Nevertheless, they are not specific nor detailed enough to examine modern smartphones, since these devices have internal memories whose removal or mirroring procedures are considered invasive and complex, due to difficulties in having direct hardware access. Furthermore, specific features of each smartphone platform have to be considered prior to acquiring its data. In order to deal with those challenges, this paper proposes a method to perform data acquisition of Android smartphones, regardless of version and manufacturer. The proposed approach takes into account existing techniques of computer and cell phone forensic examination, adapting them to specific Android characteristics, its data storage structure, popular applications and the conditions under which the device was sent to the forensic examiner. The method was defined in a broad fashion, not naming specific tools or techniques. Then, it was deployed into the examination of six Android smartphones, addressing different scenarios that an analyst might face, and was validated to perform an entire evidence acquisition

Josephson current in a four terminal superconductor - exciton condensate - superconductor system

We investigate the transport properties of a bilayer exciton condensate that is contacted by four superconducting leads. We focus on the equilibrium regime and investigate how the Josephson currents induced in the bilayer by phase biases applied to the superconducting electrodes are affected by the presence of an exciton condensate in the bulk of the system. As long as the distance between the superconducting electrodes is much larger than the exciton coherence length, the Josephson current depends only on the difference between the phase biases in the two layers. This result holds true in both short- and long-junction limits. We relate it to a novel correlated four-particle Andreev process which occurs at the superconductor - exciton condensate interface. The system we investigate provides an implementation of the supercurrent mirror proposed by Kitaev as a viable way to realize topologically protected qubits.Comment: 23 pages, 6 figures, final version accepted by PR

Quantum transport in ultracold atoms

Ultracold atoms confined by engineered magnetic or optical potentials are ideal systems for studying phenomena otherwise difficult to realize or probe in the solid state because their atomic interaction strength, number of species, density, and geometry can be independently controlled. This review focuses on quantum transport phenomena in atomic gases that mirror and oftentimes either better elucidate or show fundamental differences with those observed in mesoscopic and nanoscopic systems. We discuss significant progress in performing transport experiments in atomic gases, contrast similarities and differences between transport in cold atoms and in condensed matter systems, and survey inspiring theoretical predictions that are difficult to verify in conventional setups. These results further demonstrate the versatility offered by atomic systems in the study of nonequilibrium phenomena and their promise for novel applications.Comment: 24 pages, 7 figures. A revie