Sampling (signal processing)

Known as: Sampling frequencies, Digital samples, Sampling (information theory) 
In signal processing, sampling is the reduction of a continuous signal to a discrete signal. A common example is the conversion of a sound wave (a… (More)
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Papers overview

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Review
2017
Review
2017
Domain Adaptation for Visual Applications: A Comprehensive Survey
The aim of this paper1 is to give an overview of domain adaptation and transfer learning with a specific view on visual… (More)
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Review
2017
Review
2017
Process defects and in situ monitoring methods in metal powder bed fusion: A review
Despite continuous technological enhancements of metal Additive Manufacturing (AM) systems, the lack of process repeatability and… (More)
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Review
2017
Review
2017
Deep Learning Techniques for Music Generation - A Survey
This paper is a survey and an analysis of different ways of using deep learning (deep artificial neural networks) to generate… (More)
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Review
2017
Review
2017
A Systematic Review of Experimental Studies on Data Glyphs
We systematically reviewed 64 user-study papers on data glyphs to help researchers and practitioners gain an informed… (More)
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Review
2017
Review
2017
Multi-echo fMRI: A review of applications in fMRI denoising and analysis of BOLD signals
In recent years the field of fMRI research has enjoyed expanded technical abilities related to resolution, as well as use across… (More)
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Review
2017
Review
2017
Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo
Motivation In recent years, molecular species delimitation has become a routine approach for quantifying and classifying… (More)
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Review
2017
Review
2017
TLEL: A two-layer ensemble learning approach for just-in-time defect prediction
Context: Defect prediction is a very meaningful topic, particularly at change-level. Change-level defect prediction, which is… (More)
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Review
2017
Review
2017
Variational Autoencoder for Semi-Supervised Text Classification
Although semi-supervised variational autoencoder (SemiVAE) works in image classification task, it fails in text classification… (More)
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Highly Cited
2010
Highly Cited
2010
From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals
Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral support. In this paper… (More)
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Highly Cited
2002
Highly Cited
2002
Sampling signals with finite rate of innovation
Consider classes of signals that have a finite number of degrees of freedom per unit of time and call this number the rate of… (More)
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