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The accurate and efficient sampling of scattering parameters is addressed. A popular sampling technique is the uniform sampling combined with a straight-line interpolation for representing the continuous variation of the observable. However, this sampling ...
Sampling of alternatives has been shown to be an operational technique for the estimation of route choice models. In order to apply it, the sampling protocol generating paths must be such that the sampling probability is known, in order to correct for the ...
Sampling is a key step in the analysis of chemical compounds. It is particularly important in the environmental field, for example for wastewater effluents, wet-weather discharges or streams in which the flows and concentrations vary greatly over time. In ...
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin to a Slepian-Wolf setup, but in the sampling rather than the lossless compres ...
Besides basis expansions, frames representations play a key role in signal processing. We thus consider the problem of frame domain signal processing, which is more complex and challenging than transform domain processing. Examples of such processing aboun ...
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Some of the currently best-known approximation algorithms for network design are based on random sampling. One of the key steps of such algorithms is connecting a set of source nodes to a random subset of them. In a recent work [Eisenbrand,Grandoni,Rothvo\ ...
Clock timing jitters refer to random perturbations in the sampling time in analog-to-digital converters (ADCs). The perturbations are caused by circuit imperfections in the sampling clock. This paper analyzes the effect of sampling clock jitter on the acqu ...
We study a multichannel sampling scheme, where different channels observe scaled and shifted versions of a common bandlimited signal. The channel gains and offsets are unknown a priori, and each channel samples at sub-Nyquist rates. This setup appears in m ...
Interpolation is the means by which a continuously defined model is fit to discrete data samples. When the data samples are exempt of noise, it seems desirable to build the model by fitting them exactly. In medical imaging, where quality is of paramount im ...
We revisit the topics of near-field adaptive beamforming and source localization following an alternative approach based on a spatio- temporal spectral representation of the acoustic wave field. With the proposed method, the wave field is expressed as a se ...
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