Compressive sensing (CS) theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling, higher quality image reconstructions are often achievable. Considering that the structure of sampling protocols has such a profound impact on the quality of image reconstructions, we formulate a new sampling scheme motivated by physiological receptive field structure, loc...

The method of random sampling was introduced for the first time in the nutation nuclear quadrupole resonance (NQR) spectroscopy where the nutation spectra show characteristic singularities in the form of shoulders. The analytic formulae for complex two-dimensional (2-D) nutation NQR spectra (I = 3/2) were obtained and the condition for resolving the spectral singularities for small values of an...

We look at the benefits of using a kind of quasi-random numbers to obtain more accurate results for a given number of simulation runs. We explore a sampling method with enhanced independence in multidimensional simulations by combining the ideas of stratified sampling and Latin Hypercube sampling. We test the new sampling method by comparing it with traditional stratified sampling and Latin Hyp...

This work proposes and studies the properties of a hybrid sampling scheme that mixes independent uniform node sampling and random walk (RW)-based crawling. We show that our sampling method combines the strengths of both uniform and RW sampling while minimizing their drawbacks. In particular, our method increases the spectral gap of the random walk, and hence, accelerates convergence to the stat...

The properties of online social networks are of great interests to the general public as well as IT professionals. Often the raw data are not available and the summaries released by the service providers are sketchy. Thus sampling is needed to reveal the hidden properties and structure of the underlying network. This thesis conducts comparative studies on various sampling methods, including Ran...

This study examines the efficiency of EPI cluster sampling in assessing the prevalence of diarrhoea and dysentery. A computer was used to simulate fieldwork carried out by a survey taker. The bias and variance of prevalence estimates obtained using EPI cluster sampling were compared with those obtained using simple random sampling and cluster (stratified random) sampling. Efficiency ratios, cal...

the focus of this paper is to consider the compressed sensing problem. it is stated that the compressed sensing theory, under certain conditions, helps relax the nyquist sampling theory and takes smaller samples. one of the important tasks in this theory is to carefully design measurement matrix (sampling operator). most existing methods in the literature attempt to optimize a randomly initiali...

Born from empirical observations in nonuniformly sampled multidimensional NMR data relating to gaps between sampled points, the Poisson-gap sampling method has enjoyed widespread use in biomolecular NMR. While the majority of nonuniform sampling schemes are fully randomly drawn from probability densities that vary over a Nyquist grid, the Poisson-gap scheme employs constrained random deviates t...