Results 271 to 280 of about 12,788,874 (304)
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Biometrics, 2006
SummaryA flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values.
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SummaryA flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values.
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2021
While conducting a sample survey, a number of difficult sampling problems are encountered. One of them is the problem in estimating the population mean/total when it is rare or geographically uneven. If the population of interest is hidden or elusive, then it becomes difficult to identify it for sampling.
Raosaheb Latpate +3 more
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While conducting a sample survey, a number of difficult sampling problems are encountered. One of them is the problem in estimating the population mean/total when it is rare or geographically uneven. If the population of interest is hidden or elusive, then it becomes difficult to identify it for sampling.
Raosaheb Latpate +3 more
openaire +2 more sources
Adaptive Line Transect Sampling
Biometrics, 2002Adaptive line transect sampling offers the potential of improved population density estimation efficiency over conventional line transect sampling when populations are spatially clustered. In adaptive sampling, survey effort is increased when areas of high animal density are located, thereby increasing the number of observations.
J H, Pollard, D, Palka, S T, Buckland
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Adaptive Keyframe Sampling for Long Video Understanding
Computer Vision and Pattern RecognitionMultimodal large language models (MLLMs) have enabled open-world visual understanding by injecting visual input as extra tokens into large language models (LLMs) as contexts. However, when the visual input changes from a single image to a long video, the
Xi Tang +5 more
semanticscholar +1 more source
2019
AbstractThe abundance of rare species of plants and animals may often prove difficult to estimate due to the isolated patchy distribution of individuals. Adaptive sampling may prove more effective than other sampling strategies for such species. In adaptive cluster sampling an initial SRS of population units is selected.
David G. Hankin +2 more
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AbstractThe abundance of rare species of plants and animals may often prove difficult to estimate due to the isolated patchy distribution of individuals. Adaptive sampling may prove more effective than other sampling strategies for such species. In adaptive cluster sampling an initial SRS of population units is selected.
David G. Hankin +2 more
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Adaptive Rejection Sampling for Gibbs Sampling
Applied Statistics, 1992Summary: We propose a method for rejection sampling from any univariate log- concave probability density function. The method is adaptive: as sampling proceeds, the rejection envelope and squeezing function are converge to the density function. The technique is intended for situations where evaluation of the density is computationally expensive, in ...
Gilks, W. R., Wild, P.
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Mobile Sensor Networks and Control: Adaptive Sampling of Spatiotemporal Processes
Annu. Rev. Control. Robotics Auton. Syst., 2020The control of mobile sensor networks uses sensor measurements to update a model of an unknown or estimated process, which in turn guides the collection of subsequent measurements—a feedback control framework called adaptive sampling.
D. Paley, A. Wolek
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A 61-nW Level-Crossing ADC With Adaptive Sampling for Biomedical Applications
IEEE Transactions on Circuits and Systems - II - Express Briefs, 2019An ultra-low-power level-crossing analog-to-digital converter (LC-ADC) with on-chip adaptive sampling is presented. Different from conventional ADCs based on Nyquist sampling, LC-ADC utilizes sparsity of signals for low power data acquisition.
Yuting Hou +6 more
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, 2020
Surrogate models can be used to approximate complex systems at a reduced cost and are widely used when data generation is expensive or time consuming. The accuracy of these models is dependent on the samples used to create them.
Andrew L. Kaminsky, Yi Wang, K. Pant
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Surrogate models can be used to approximate complex systems at a reduced cost and are widely used when data generation is expensive or time consuming. The accuracy of these models is dependent on the samples used to create them.
Andrew L. Kaminsky, Yi Wang, K. Pant
semanticscholar +1 more source
1971 IEEE Conference on Decision and Control, 1971
Discussion of digital adaptive sampling, which is consistently better than fixed sampling in noise-free cases. Adaptive sampling is shown to be feasible and, it is considered, should be studied further. It should be noted that adaptive sampling is a class of variable rate sampling in which the variability depends on system signals. Digital rather than
Gerald Breazeale, Lloyd Jones
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Discussion of digital adaptive sampling, which is consistently better than fixed sampling in noise-free cases. Adaptive sampling is shown to be feasible and, it is considered, should be studied further. It should be noted that adaptive sampling is a class of variable rate sampling in which the variability depends on system signals. Digital rather than
Gerald Breazeale, Lloyd Jones
openaire +1 more source