Results 211 to 220 of about 83,645 (264)
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2011
The search for similarities in large data sets has a very important role in many scientific fields. It permits to classify several types of data without an explicit information about it. In many cases researchers use analysis methodologies such as clustering to classify data with respect to the patterns and conditions together.
Ekaterina Nosova +3 more
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The search for similarities in large data sets has a very important role in many scientific fields. It permits to classify several types of data without an explicit information about it. In many cases researchers use analysis methodologies such as clustering to classify data with respect to the patterns and conditions together.
Ekaterina Nosova +3 more
openaire +4 more sources
Resampled Regenerative Estimators
ACM Transactions on Modeling and Computer Simulation, 2015We discuss some estimators for simulations of processes having multiple regenerative sequences. The estimators are obtained by resampling trajectories without and with replacement, which correspond to a type of U -statistic and a type of V -statistic, respectively. The U
James M. Calvin, Marvin K. Nakayama
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WIREs Data Mining and Knowledge Discovery, 2012
AbstractResampling methods are statistical procedures that reuse the sample data for the purpose of statistical inference. However, they do not require parametric assumptions that may be difficult to verify in practice. This focus article describes four resampling techniques, the bootstrap, the jackknife, crossâvalidation, and permutation tests ...
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AbstractResampling methods are statistical procedures that reuse the sample data for the purpose of statistical inference. However, they do not require parametric assumptions that may be difficult to verify in practice. This focus article describes four resampling techniques, the bootstrap, the jackknife, crossâvalidation, and permutation tests ...
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On resampling schemes for polytopes
Journal of Applied Probability, 2019AbstractThe convex hull of a sample is used to approximate the support of the underlying distribution. This approximation has many practical implications in real life. To approximate the distribution of the functionals of convex hulls, asymptotic theory plays a crucial role.
Weinan Qi, Mahmoud Zarepour
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IEEE Transactions on Computers, 1982
Due to advances in VLSI technology, large scale arrays of microprocessors forming parallel processing systems have become feasible. The use of such a microprocessor array operating in the SIMD (single instruction stream-multiple data stream) mode to perform image resampling is explored.
Michael R. Warpenburg, Leah J. Siegel
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Due to advances in VLSI technology, large scale arrays of microprocessors forming parallel processing systems have become feasible. The use of such a microprocessor array operating in the SIMD (single instruction stream-multiple data stream) mode to perform image resampling is explored.
Michael R. Warpenburg, Leah J. Siegel
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Resampling for wireless access
Proceedings of PIMRC '96 - 7th International Symposium on Personal, Indoor, and Mobile Communications, 2002The well known problem among most random access protocols in wireless networks is that the throughput drops rapidly in heavy loads. To cope with this problem, one has to control to the load offered to a network. Unlike the traditional backoff policy in Ethernet where backoff occurs after collision, we propose various control schemes based on the new ...
Ming-Young You, Cheng-Shang Chang
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On Importance Resampling for the Bootstrap
Biometrika, 1991SUMMARY We introduce an empirical method of importance resampling, which does not require analytical calculation of the resampling probabilities. Our method can easily be used as part of a general algorithm for Monte Carlo calculation of bootstrap confidence intervals and hypothesis tests.
KIM-ANH DO, PETER HALL
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A Scalable Resampling Architecture
IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference, 2007This paper proposes a resampler architecture which employs the filtering the input signal with a FIR filter whose coefficients depend on the phase of the interpolated sample relative to the input samples. The novelty of this architecture consists in generating the coefficients by using linear interpolation between a number of predefined coefficient ...
Mihail Petrov, Manfred Glesner
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Resampling for Face Recognition
2003A number of applications require robust human face recognition under varying environmental lighting conditions and different facial expressions, which considerably vary the appearance of human face. However, in many face recognition applications, only a small number of training samples for each subject are available; these samples are not able to ...
Xiaoguang Lu, Anil K. Jain 0001
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Resampling on a Pseudohexagonal Grid
CVGIP: Graphical Models and Image Processing, 1994Abstract This paper investigates resampling techniques on a pseudohexagonal grid. Hexagonal grids are known to be advantageous in many respects for sampling and representing digital images in various computer vision and graphics applications. Currently, a real hexagonal grid device is still difficult to find.
Innchyn Her, Chi-Tseng Yuan
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