Results 41 to 50 of about 3,116,070 (323)
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing [PDF]
IEEE Transactions on Image Processing, 2018 Hyperspectral imagery collected from airborne or satellite sources inevitably suffers from spectral variability, making it difficult for spectral unmixing to accurately estimate abundance maps. The classical unmixing model, the linear mixing model (LMM),
D. Hong +3 more
semanticscholar +1 more source
Frontiers in Physiology, 2020 Sub-threshold (imperceptible) vibration, applied to parts of the body, impacts how people move and perceive our world. Could this idea help someone who has lost part of their limb?
Aaron D. Likens +7 more
doaj +1 more source
Increasing precipitation variability on daily-to-multiyear time scales in a warmer world
Science Advances, 2021 Rainfall will become more variable from day to day and year to year in global wet regions under future warming. The hydrological cycle intensifies under global warming with precipitation increases.
Wenxia Zhang +7 more
semanticscholar +1 more source
, 2015 While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model ...
a. +11 more
semanticscholar +1 more source
Real-Variable Theory of Local Variable Hardy Spaces [PDF]
arXiv, 2021 In this paper, we give a complete real-variable theory of local variable Hardy spaces. First, we present various real-variable characterizations in terms of several local maximal functions. Next, the new atomic and the finite atomic decomposition for the local variable Hardy spaces are established.
arxiv
Depicting deterministic variables within directed acyclic graphs (DAGs): An aid for identifying and interpreting causal effects involving tautological associations, compositional data, and composite variables [PDF]
arXiv, 2022 Deterministic variables are variables that are fully explained by one or more parent variables. They commonly arise when a variable has been algebraically constructed from one or more parent variables, as with composite variables, and in compositional data, where the 'whole' variable is determined from its 'parts'.
arxiv
An information criterion for auxiliary variable selection in incomplete data analysis [PDF]
, 2019 Statistical inference is considered for variables of interest, called primary variables, when auxiliary variables are observed along with the primary variables. We consider the setting of incomplete data analysis, where some primary variables are not observed.
arxiv +1 more source
Frontiers in Physiology, 2018 The fractal analysis of stride-to-stride fluctuations in walking has become an integral part of human gait research. Fractal analysis of stride time intervals can provide insights into locomotor function and dysfunction, but its application requires a ...
Vivien Marmelat +2 more
doaj +1 more source
Gradient and Hessian of functions with non-independent variables [PDF]
arXiv, 2023 Mathematical models are sometime given as functions of independent input variables and equations or inequations connecting the input variables. A probabilistic characterization of such models results in treating them as functions with non-independent variables.
arxiv
Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance
Nature, 2017 Therapies that target signalling molecules that are mutated in cancers can often have substantial short-term effects, but the emergence of resistant cancer cells is a major barrier to full cures.
Sydney M. Shaffer +16 more
semanticscholar +1 more source