Sequential Sampling and Estimation of Approximately Bandlimited Graph Signals [PDF]
Sensors, 2021 Graph signal sampling has been widely studied in recent years, but the accurate signal models required by most of the existing sampling methods are usually unavailable prior to any observations made in a practical environment. In this paper, a sequential
Sijie Lin, Ke Xu, Hui Feng, Bo Hu
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MaxEnt Queries and Sequential Sampling [PDF]
AIP Conference Proceedings, 2000 In this paper we pose the question: After gathering N data points, at what value of the control parameter should the next measurement be done? We propose an on-line algorithm which samples optimally by maximizing the gain in information on the ...
Caticha, Nestor, Riegler, Peter
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Spatial distribution and fixed-precision sequential sampling plans for Popillia japonica (Coleoptera: Scarabaeidae) adults in primocane raspberry: influence of foliar insecticides [PDF]
Frontiers in Insect ScienceThe Japanese beetle, Popillia japonica Newman (Coleoptera: Scarabaeidae), an invasive species from northern Japan, was first detected in Minnesota in 1968.
Adam G. Toninato +2 more
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Sequential sampling of visual objects during sustained attention. [PDF]
PLoS Biology, 2017 In a crowded visual scene, attention must be distributed efficiently and flexibly over time and space to accommodate different contexts. It is well established that selective attention enhances the corresponding neural responses, presumably implying that
Jianrong Jia +3 more
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Sequential sampling strategy for extreme event statistics in nonlinear dynamical systems. [PDF]
Proc Natl Acad Sci U S A, 2018 We develop a method for the evaluation of extreme event statistics associated with nonlinear dynamical systems, using a small number of samples. From an initial dataset of design points, we formulate a sequential strategy that provides the 'next-best ...
Mohamad MA, Sapsis TP.
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ASAMS: An Adaptive Sequential Sampling and Automatic Model Selection for Artificial Intelligence Surrogate Modeling [PDF]
Sensors, 2020 Surrogate Modeling (SM) is often used to reduce the computational burden of time-consuming system simulations. However, continuous advances in Artificial Intelligence (AI) and the spread of embedded sensors have led to the creation of Digital Twins (DT),
Carlos A. Duchanoy +2 more
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Sequential sampling model for multiattribute choice alternatives with random attention time and processing order [PDF]
Frontiers in Human Neuroscience, 2014 A sequential sampling model for multiattribute binary choice options, called Multiattribute attention switching (MAAS) model, assumes a separate sampling process for each attribute.
Adele eDiederich, Peter eOswald
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Multilevel Fixed and Sequential Acceptance Sampling: The R Package MFSAS [PDF]
Journal of Statistical Software, 2011 Multilevel acceptance sampling for attributes is used to decide whether a lot from an incoming shipment or outgoing production is accepted or rejected when the product has multiple levels of product quality or multiple types of (mutually exclusive ...
Aaron Childs, Yalin Chen
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Development of surrogate models in reliability-based design optimization: A review
Mathematical Biosciences and Engineering, 2021 Reliability-based design optimization (RBDO) is applied to handle the unavoidable uncertainties in engineering applications. To alleviate the huge computational burden in reliability analysis and design optimization, surrogate models are introduced to ...
Xiaoke Li +6 more
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Two–step sequential sampling [PDF]
Statistica Neerlandica, 2002 Choosing the sample size in advance is a familiar problem: often, additional observations appear to be desirable. The final sample size then becomes a random variable, which has rather serious consequences.Two such sample extension situations will be considered here.
Moors, J.J.A., Strijbosch, L.W.G.
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