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This communication addresses the problem of any simulation tool: the accurate and efficient sampling of a physical observable with respect to a parameter. A popular sampling technique is the uniform sampling combined with a straight-line interpolation for ...
Nowadays digital signal processing systems used for radar applications, communication systems or RF measurement equipments, require very high sample-rates. Sometimes these sample-rates are beyond the possibilities offered by conventional ADCs. To overcome ...
We study the spatial-temporal sampling of a linear diffusion field, and show that it is possible to compensate for insufficient spatial sampling densities by oversampling in time. Our work is motivated by the following issue often encountered in sensor net ...
As the World Wide Web is growing rapidly, it is getting increasingly challenging to gather representative information about it. Instead of crawling the web exhaustively one has to resort to other techniques like sampling to determine the properties of the ...
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquiring sparse or compressible signals. Instead of taking N periodic samples, we measure M < N inner products with random vectors and then recover the signal via a sparsity-seeki ...
Given two camera calibrations, this report presents a closed form algorithm that computes a sequence of 3D points such that they all project to a single location on one camera and that their projection forms a uniformly sampled line on the other camera. ...
We report on a search for the X(1812) state in the decay B-+/--> K-+/-omega phi with a data sample of 657x10(6) BB pairs collected with the Belle detector at the KEKB e(+)e(-) collider. No significant signal is observed. An upper limit ...
We address the problem of generalized sampling and reconstruction of finite-rate-of-innovation signals. Specifically, we consider the problem of sampling streams of Dirac impulses and propose a two-channel method that enables fast, local reconstruction und ...
It is well known that the support of a sparse signal can be recovered from a small number of random projections. However, in the presence of noise all known sufficient conditions require that the per-sample signal-to-noise ratio (SNR) grows without bound w ...
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In this paper we consider the problem of sampling far below the Nyquist rate signals that are sparse linear superpositions of shifts of a known, potentially wide-band, pulse. This signal model is key for applications such as Ultra Wide Band (UWB) communica ...