Sparse sampling of signal innovations

Sparse sampling of continuous-time sparse signals is addressed. In particular, it is shown that sampling at the rate of innovation is possible, in some sense applying Occam's razor to the sampling of sparse signals. The noisy case is analyzed and solved, proposing methods reaching the optimal performance given by the Cramer-Rao bounds. Finally, a number of applications have been discussed where sparsity can be taken advantage of. The comprehensive coverage given in this article should lead to further research in sparse sampling, as well as new applications. One main application to use the theory presented in this article is ultra-wide band (UWB) communications

Disruption of beta cell acetyl-CoA carboxylase-1 in mice impairs insulin secretion and beta cell mass

Aims/hypothesis: Pancreatic beta cells secrete insulin to maintain glucose homeostasis, and beta cell failure is a hallmark of type 2 diabetes. Glucose triggers insulin secretion in beta cells via oxidative mitochondrial pathways. However, it also feeds mitochondrial anaplerotic pathways, driving citrate export and cytosolic malonyl-CoA production by the acetyl-CoA carboxylase 1 (ACC1) enzyme. This pathway has been proposed as an alternative glucose-sensing mechanism, supported mainly by in vitro data. Here, we sought to address the role of the beta cell ACC1-coupled pathway in insulin secretion and glucose homeostasis in vivo. Methods: Acaca, encoding ACC1 (the principal ACC isoform in islets), was deleted in beta cells of mice using the Cre/loxP system. Acaca floxed mice were crossed with Ins2cre mice (βACC1KO; life-long beta cell gene deletion) or Pdx1creER mice (tmx-βACC1KO; inducible gene deletion in adult beta cells). Beta cell function was assessed using in vivo metabolic physiology and ex vivo islet experiments. Beta cell mass was analysed using histological techniques. Results: βACC1KO and tmx-βACC1KO mice were glucose intolerant and had defective insulin secretion in vivo. Isolated islet studies identified impaired insulin secretion from beta cells, independent of changes in the abundance of neutral lipids previously implicated as amplification signals. Pancreatic morphometry unexpectedly revealed reduced beta cell size in βACC1KO mice but not in tmx-βACC1KO mice, with decreased levels of proteins involved in the mechanistic target of rapamycin kinase (mTOR)-dependent protein translation pathway underpinning this effect. Conclusions/interpretation: Our study demonstrates that the beta cell ACC1-coupled pathway is critical for insulin secretion in vivo and ex vivo and that it is indispensable for glucose homeostasis. We further reveal a role for ACC1 in controlling beta cell growth prior to adulthood.</p

Progressive Meshes in an Operational Rate-Distortion Sense with Application to Terrain Data

This paper presents an efficient simplification method for regular meshes obtained with a binary subdivision scheme. Our mesh connectivity is constrained with a quadtree data structure. We propose a quadtree built especially for this class of meshes having a constant-time traversal property. We introduce a rate-distortion (RD) framework to decimate the mesh and build a progressive representation for the model. We propose to achieve the RD-optimal solutions for our quadtree-restricted setting: to obtain the optimal solutions, we show how to find the vertex in the quadtree yielding the best RD trade-off and then perform optimizations at variable rate, where the rate is given by a cost function (for example the number of triangles). All previous methods are restricted to constant rate optimization only. We compare the optimal approach to its greedy counterpart. We give computationally optimal formulations for all our algorithms on the quadtree. We apply our technique to a large dataset of terrains and give extensive experimental results

On the Multiterminal Rate-Distortion Function for Acoustic Sensing

We consider the rate-distortion problem for recording a Gaussian acoustic field with an array of sensors equipped with microphones. Our analysis is based on the field's spatiotemporal correlation structure, which is induced by the physics of sound propagation. Under certain assumptions about the spectrum of the wave kernel, we determine the rate-distortion functions for various distributed source coding schemes and sampling lattices. Our results also include an answer to the multiterminal rate-distortion problem for the setup considered in the paper

On Sampling and Coding for Distributed Acoustic Sensing

The issue of how to efficiently represent the data collected by a network of microphones recording spatio-temporal acoustic wave fields is addressed. Each sensor node in the network samples the sound field, quantizes the samples and transmits the encoded samples to some central unit, which computes an estimate of the original sound field based on the information received from all the microphones. Our analysis is based on the spectral properties of the sound field, which are induced by the physics of wave propagation and have a significant impact on the efficiency of the chosen sampling lattice and coding scheme. As field acquisition by a sensor network typically implies spatio-temporal sampling of the field, a multidimensional sampling theorem for homogeneous random fields with compactly supported spectral measures is proved. To assess the loss of information implied by source coding, rate distortion functions for various coding schemes and sampling lattices are determined. In particular, centralized coding, independent coding and some multiterminal schemes are compared. Under the assumption of spectral whiteness of the sound field, it is shown that sampling with a quincunx lattice followed by independent coding is optimal as it achieves the lower bound given by centralized coding

A Stochastic Model for Video and its Information Rates

We propose a stochastic model for video and compute its information rates. The model has two sources of information representing ensembles of camera motion and visual scene data (i.e. "realities"). The sources of information are combined generating a vector process that we study in detail. Both lossless and lossy information rates are derived. The model is further extended to account for realities that change over time. We derive bounds on the lossless and lossy information rates for this dynamic reality model, stating conditions under which the bounds are tight. Experiments with synthetic sources suggest that in the presence of scene motion, simple hybrid coding using motion estimation with DPCM can be suboptimal relative to the true rate-distortion bound

Practical solution to the Monte Carlo sign problem: Realistic calculations of 54Fe

We present a practical solution to the "sign problem" in the auxiliary field Monte Carlo approach to the nuclear shell model. The method is based on extrapolation from a continuous family of problem-free Hamiltonians. To demonstrate the resultant ability to treat large shell-model problems, we present results for 54Fe in the full fp-shell basis using the Brown-Richter interaction. We find the Gamow-Teller beta^+ strength to be quenched by 58% relative to the single-particle estimate, in better agreement with experiment than previous estimates based on truncated bases.Comment: 11 pages + 2 figures (not included

Robust Array Calibration Using Time Delays with Application to Ultrasound Tomography

Accurate calibration is a requirement of many array signal processing techniques. We investigate the calibration of a transducer array using time delays. We derive a strategy based on the mean square error criterion and discuss how time delays that are not available can be interpolated from existing ones. The proposed method is made robust to noise and model mismatch by means of a novel iterative technique for distance matrix denoising. The convergence of the method is proved. Finally, the accuracy of the proposed calibration algorithm is assessed both in simulated scenarios and using experimental data obtained from an ultrasound scanner designed for breast cancer detection

Data compression and harmonic analysis

In this paper we review some recent interactions between harmonic analysis and data compression. The story goes back of course to Shannon’