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In this paper, we show how to estimate the asymptotic (conditional) covariance matrix, which appears in central limit theorems in high-frequency estimation of asset return volatility. We provide a recipe for the estimation of this matrix by…

Econometrics · Economics 2026-01-26 Kim Christensen , Mark Podolskij , Nopporn Thamrongrat , Bezirgen Veliyev

In light of the ever-increasing demand for new spectral bands and the underutilization of those already allocated, the concept of Cognitive Radio (CR) has emerged. Opportunistic users could exploit temporarily vacant bands after detecting…

Information Theory · Computer Science 2015-06-17 Deborah Cohen , Yonina C. Eldar

The theory of co-prime arrays has been studied in the past. Nyquist rate estimation of second order statistics using the combined difference set was demonstrated with low latency. This paper proposes a novel method to reconstruct the second…

Signal Processing · Electrical Eng. & Systems 2020-10-05 Usham V. Dias

We study the impact of sampling theorems on the fidelity of sparse image reconstruction on the sphere. We discuss how a reduction in the number of samples required to represent all information content of a band-limited signal acts to…

Information Theory · Computer Science 2013-04-17 J. D. McEwen , G. Puy , J. -Ph. Thiran , P. Vandergheynst , D. Van De Ville , Y. Wiaux

Advances of information-theoretic understanding of sparse sampling of continuous uncoded signals at sampling rates exceeding the Landau rate were reported in recent works. This work examines sparse sampling of coded signals at sub-Landau…

Information Theory · Computer Science 2013-03-04 Michael Peleg , Shlomo Shamai

Sonography techniques use multiple transducer elements for tissue visualization. Signals detected at each element are sampled prior to digital beamforming. The required sampling rates are up to 4 times the Nyquist rate of the signal and…

Information Theory · Computer Science 2012-12-21 T. Chernyakova , Y. C. Eldar , R. Amit

The sensing matrix of a compressive system impacts the stability of the associated sparse recovery problem. In this paper, we study the sensing matrix of the modulated wideband converter, a recently proposed system for sub-Nyquist sampling…

Information Theory · Computer Science 2009-09-29 Moshe Mishali , Yonina C. Eldar

Undersampled images, such as those produced by the HST WFPC-2, misrepresent fine-scale structure intrinsic to the astronomical sources being imaged. Analyzing such images is difficult on scales close to their resolution limits and may…

Astrophysics · Physics 2009-10-31 Tod R. Lauer

We advocate an optimization procedure for variable density sampling in the context of compressed sensing. In this perspective, we introduce a minimization problem for the coherence between the sparsity and sensing bases, whose solution…

Information Theory · Computer Science 2011-09-29 Gilles Puy , Pierre Vandergheynst , Yves Wiaux

The field of compressed sensing has shown that a sparse but otherwise arbitrary vector can be recovered exactly from a small number of randomly constructed linear projections (or samples). The question addressed in this paper is whether an…

Information Theory · Computer Science 2010-01-26 Galen Reeves , Michael Gastpar

Multi-rate asynchronous sub-Nyquist sampling (MASS) is proposed for wideband spectrum sensing. Corresponding spectral recovery conditions are derived and the probability of successful recovery is given. Compared to previous approaches, MASS…

Information Theory · Computer Science 2013-03-11 Hongjian Sun , Wei-Yu Chiu , Jing Jiang , Arumugam Nallanathan , H. Vincent Poor

A sampling method by using scattering amplitude is proposed for shape and location reconstruction in inverse acoustic scattering problems. Only matrix multiplication is involved in the computation, thus the novel sampling method is very…

Numerical Analysis · Mathematics 2017-09-13 Xiaodong Liu

Recently, there was a substantial progress in the problem of sampling recovery on function classes with mixed smoothness. Mostly, it has been done by proving new and sometimes optimal upper bounds for both linear sampling recovery and for…

Numerical Analysis · Mathematics 2025-05-29 A. Gasnikov , V. Temlyakov

In this paper, we consider the problem of recovering a compactly supported multivariate function from a collection of pointwise samples of its Fourier transform taken nonuniformly. We do this by using the concept of weighted Fourier frames.…

Numerical Analysis · Mathematics 2015-09-08 Ben Adcock , Milana Gataric , Anders C. Hansen

The paper introduces a framework for the recoverability analysis in compressive sensing for imaging applications such as CI cameras, rapid MRI and coded apertures. This is done using the fact that the Spherical Section Property (SSP) of a…

Information Theory · Computer Science 2012-12-07 Mahdi S. Hosseini , Konstantinos N. Plataniotis

This paper describes performance bounds for compressed sensing (CS) where the underlying sparse or compressible (sparsely approximable) signal is a vector of nonnegative intensities whose measurements are corrupted by Poisson noise. In this…

Information Theory · Computer Science 2015-05-14 Maxim Raginsky , Rebecca M. Willett , Zachary T. Harmany , Roummel F. Marcia

This contribution proposes a two stage strategy to allow for phase retrieval in state of the art sub-Nyquist sampling schemes for sparse multiband signals. The proposed strategy is based on data acquisition via modulated wideband converters…

Information Theory · Computer Science 2015-09-29 Çağkan Yapar , Volker Pohl , Holger Boche

Signals comprised of a stream of short pulses appear in many applications including bio-imaging and radar. The recent finite rate of innovation framework, has paved the way to low rate sampling of such pulses by noticing that only a small…

Information Theory · Computer Science 2015-05-18 Ronen Tur , Yonina C. Eldar , Zvi Friedman

Phase retrieval seeks to recover a complex signal from amplitude-only measurements, a challenging nonlinear inverse problem. Current theory and algorithms often ignore signal priors. By contrast, we evaluate here a variety of image priors…

Image and Video Processing · Electrical Eng. & Systems 2025-09-19 Stanislas Ducotterd , Zhiyuan Hu , Michael Unser , Jonathan Dong

A different compressive sensing framework, convolution with white noise waveform followed by subsampling at fixed (not randomly selected) locations, is studied in this paper. We show that its recoverability for sparse signals depends on the…

Optimization and Control · Mathematics 2009-09-30 Yin Xiang , Lianlin Li , Fang Li