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Resampling is an operation costly in calculation time and accuracy. It regularizes irregular sampling, replacing N data by N periodic estimations. This stage can be suppressed, using formulas built with incoming data and completed by…

Data Analysis, Statistics and Probability · Physics 2019-05-28 Bernard Lacaze

It is well known that the linear stability of solutions of partial differential equations which are integrable can be very efficiently investigated by means of spectral methods. We present here a direct construction of the eigenmodes of the…

Exactly Solvable and Integrable Systems · Physics 2018-06-18 Antonio Degasperis , Sara Lombardo , Matteo Sommacal

Multi-dimensional magnetic resonance spectroscopy is an important tool for studying molecular structures, interactions and dynamics in bio-engineering. The data acquisition time, however, is relatively long and non-uniform sampling can be…

Medical Physics · Physics 2017-01-26 Xiaobo Qu , Jiaxi Ying , Jian-Feng Cai , Zhong Chen

A class of parametric functions formed by alternating compositions of multivariate polynomials and rectification style monomial maps is studied (the layer-wise exponents are treated as fixed hyperparameters and are not optimized). For this…

Optimization and Control · Mathematics 2026-02-13 Shravan Mohan

Bandpass signals are an important sub-class of bandlimited signals that naturally arise in a number of application areas but their high-frequency content poses an acquisition challenge. Consequently, "Bandpass Sampling Theory" has been…

Information Theory · Computer Science 2023-07-12 Gal Shtendel , Dorian Florescu , Ayush Bhandari

We consider a class of inverse problems defined by a nonlinear map from parameter or model functions to the data. We assume that solutions exist. The space of model functions is a Banach space which is smooth and uniformly convex; however,…

Functional Analysis · Mathematics 2015-05-30 Maarten V. de Hoop , Lingyun Qiu , Otmar Scherzer

Sampling of a spatiotemporal field for environmental sensing is of interest. Traditionally, a few fixed stations or sampling locations aid in the reconstruction of the spatial field. Recently, there has been an interest in mobile sensing…

Information Theory · Computer Science 2017-12-06 Sudeep Salgia , Animesh Kumar

We consider the first order periodic systems perturbed by a $2N\ts 2N$ matrix-valued periodic potential on the real line. The spectrum of this operator is absolutely continuous and consists of intervals separated by gaps. We define the…

Spectral Theory · Mathematics 2007-05-23 Evgeny Korotyaev

We consider univariate regression estimation from an individual (non-random) sequence $(x_1,y_1),(x_2,y_2), ... \in \real \times \real$, which is stable in the sense that for each interval $A \subseteq \real$, (i) the limiting relative…

Probability · Mathematics 2008-06-19 Gusztav Morvai , Sanjeev R. Kulkarni , Andrew B. Nobel

We address the problem of estimating time and frequency shifts of a known waveform in the presence of multiple measurement vectors (MMVs). This problem naturally arises in radar imaging and wireless communications. Specifically, a signal…

Information Theory · Computer Science 2021-03-01 Maral Safari , Sajad Daei , Farzan Haddadi

This article deals with adaptive nonparametric estimation for L\'evy processes observed at low frequency. For general linear functionals of the L\'evy measure, we construct kernel estimators, provide upper risk bounds and derive rates of…

Statistics Theory · Mathematics 2014-07-15 Johanna Kappus

In this paper, we discuss to the nonuniform sampling problem in principal shift-invariant subspaces of mixed Lebesgue spaces. We proposed a fast reconstruction algorithm which allows to exactly reconstruct the functions in the principal…

Functional Analysis · Mathematics 2018-01-26 Qingyue Zhang

We study the sampling of spatial fields using sensors that are location-unaware but deployed according to a known statistical distribution. It has been shown that uniformly distributed location-unaware sensors cannot infer bandlimited…

Information Theory · Computer Science 2016-12-01 Ankur Mallick , Animesh Kumar

This paper is concerned with stability analysis of nonlinear time-varying systems by using Lyapunov function based approach. The classical Lyapunov stability theorems are generalized in the sense that the time-derivative of the Lyapunov…

Dynamical Systems · Mathematics 2017-08-18 Bin Zhou

We describe a "spatio-spectral" deconvolution algorithm for wide-band imaging in radio interferometry. In contrast with the existing multi-frequency reconstruction algorithms, the proposed method does not rely on a model of the…

Instrumentation and Methods for Astrophysics · Physics 2016-03-01 André Ferrari , Jérémy Deguignet , Chiara Ferrari , David Mary , Antony Schutz , Oleg Smirnov

Within the framework of linear elasticity we assume the availability of internal full-field measurements of the continuum deformations of a non-homogeneous isotropic solid. The aim is the quantitative reconstruction of the associated…

Analysis of PDEs · Mathematics 2015-06-17 Guillaume Bal , Cédric Bellis , Sébastien Imperiale , François Monard

In this paper, we consider sampling and reconstruction of signals in a reproducing kernel subspace of $L^p(\Rd), 1\le p\le \infty$, associated with an idempotent integral operator whose kernel has certain off-diagonal decay and regularity.…

Information Theory · Computer Science 2010-08-26 M. Zuhair Nashed , Qiyu Sun

In this paper, we numerically investigate an inverse problem of recovering the potential term in a fractional Sturm-Liouville problem from one spectrum. The qualitative behaviors of the eigenvalues and eigenfunctions are discussed, and…

Numerical Analysis · Mathematics 2015-06-04 Bangti Jin , William Rundell

We use the inverse pressure concept to estimate the stable dimension for hyperbolic non-invertible maps which are conformal in the stable fibers. The non-invertible case is different than the diffeomorphism case. In particular we show that…

Dynamical Systems · Mathematics 2008-11-21 Eugen Mihailescu , Mariusz Urbanski

To increase the flexibility and scalability of deep neural networks for image reconstruction, a framework is proposed based on bandpass filtering. For many applications, sensing measurements are performed indirectly. For example, in…

Computer Vision and Pattern Recognition · Computer Science 2018-11-27 Joseph Y. Cheng , Feiyu Chen , Marcus T. Alley , John M. Pauly , Shreyas S. Vasanawala