Results 1 to 10 of about 77,058 (245)
The Megopolis resampler: Memory coalesced resampling on GPUs [PDF]
Digital Signal Processing, 2022 The resampling process employed in widely used methods such as Importance Sampling (IS), with its adaptive extension (AIS), are used to solve challenging problems requiring approximate inference; for example, non-linear, non-Gaussian state estimation problems.
Joshua A. Chesser +2 more
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Experimenting With the Past to Improve Environmental Monitoring
Frontiers in Ecology and Evolution, 2021 Long-term monitoring programs are a fundamental part of both understanding ecological systems and informing management decisions. However, there are many constraints which might prevent monitoring programs from being designed to consider statistical ...
Easton R. White +2 more
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PREDICTION OF SURVIVAL OF HEART FAILURE PATIENTS USING RANDOM FOREST
Pilar Nusa Mandiri, 2020 Human survival, one of the roles that is controlled by the heart, makes the heart need to be guarded and be aware of its damage. Heart failure is the final stage of all heart disease.
Sri Rahayu +5 more
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Analysis of sparse data in pharmacokinetic studies
Фармакокинетика и Фармакодинамика, 2020 Performing pharmacokinetic and statistical analysis in the case of sparse data presents significant difficulties. Using the example of the pharmacokinetic (PK) study of resveratrol in mice, the resampling method was allowed us to obtain individual PK ...
I. I. Miroshnichenko +3 more
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Sampling sufficiency for mechanical properties of wood
Maderas: Ciencia y Tecnología, 2023 Based on most recently published studies, there is a large variability in both the mechanical properties of wood and sample sizes selected to evaluate them.
Arthur B. Aramburu +3 more
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Adaptive memory-based single distribution resampling for particle filter
Journal of Big Data, 2017 The restrictions that are related to using single distribution resampling for some specific computing devices’ memory gives developers several difficulties as a result of the increased effort and time needed for the development of a particle filter. Thus,
Wan Mohd Yaakob Wan Bejuri +4 more
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Winter Holts Oscillatory Method: A New Method of Resampling in Time Series. [PDF]
South Asian Journal of Management Sciences, 2016 The core proposition behind this research is to create innovative methods of bootstrapping that can be applied in time series data. In order to find new methods of bootstrapping, various methods were reviewed; The data of automotive Sales, Market Shares ...
Muhammad Imtiaz Subhani +1 more
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FDA-MIMO Radar Moving Target Detection Based on Doppler Spread Compensation
Leida xuebao, 2022 When Frequency Diverse Array and Multiple-Input Multiple-Output (FDA-MIMO) radar detects moving targets, the frequency offset between transmitting arrays is coupled with the target velocity, resulting in severe Doppler spread in the slow time dimension ...
Shunsheng ZHANG, Meihui LIU, Wenqin WANG
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Fingerprint resampling: A generic method for efficient resampling [PDF]
Scientific Reports, 2015 AbstractIn resampling methods, such as bootstrapping or cross validation, a very similar computational problem (usually an optimization procedure) is solved over and over again for a set of very similar data sets. If it is computationally burdensome to solve this computational problem once, the whole resampling method can become unfeasible.
Mestdagh, Merijn +3 more
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Frontiers in Bioengineering and Biotechnology, 2020 Injury risk curves (IRCs) represent the quantification of risk of adverse outcomes, such as a bone fracture, quantified by a biomechanical metric such as force or deflection.
Anjishnu Banerjee +4 more
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