Results 51 to 60 of about 133,952 (267)
Drones, 2023 This paper focuses on distributed state estimation (DSE) and unmanned aerial vehicle (UAV) path optimization for target tracking. First, a diffusion cubature Kalman filter with intermittent measurements based on covariance intersection (DCKFI-CI) is ...
Shen Wang +3 more
doaj +1 more source
Analysis error covarianceversusposterior covariance in variational data assimilation [PDF]
Quarterly Journal of the Royal Meteorological Society, 2012 AbstractThe problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function (analysis). The data contain errors (observation and background errors); hence there is an error in the analysis.
Gejadze, Igor +2 more
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Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay +15 more
wiley +1 more source
Classification of Gaussian spatio-temporal data with stationary separable covariances
Nonlinear Analysis, 2021 The novel approach to classification of spatio-temporal data based on Bayes discriminant functions is developed. We focus on the problem of supervised classifying of the spatiotemporal Gaussian random field (GRF) observation into one of two classes ...
Marta Karaliutė, Kęstutis Dučinskas
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Arthritis Care &Research, EarlyView.Objective Somatic items used in depression assessments can potentially overlap with symptoms related to physical illness, including systemic sclerosis (SSc). No studies have looked at whether somatic depression items may be influenced by diffuse versus limited SSc disease subtypes, which are associated with varying degrees of symptom presentation.
Sophie Hu +110 more
wiley +1 more source
Estimating model error covariance matrix parameters in extended Kalman filtering [PDF]
Nonlinear Processes in Geophysics, 2014 The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user.
A. Solonen +4 more
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dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
wiley +1 more source
Considering the impact of observation error correlation in ensemble square-root Kalman filter [PDF]
Brazilian Journal of Oceanography, 2019 Data assimilation has been developed into an effective technology that can utilize a large number of multi-source unconventional data. It cannot only provide the initial field for the ocean numerical prediction model, but also construct the ocean ...
Shaodong Zang, Jichao Wang
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Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Spatial Regression with Covariate Measurement Error: A Semiparametric Approach [PDF]
Biometrics, 2016 Summary Spatial data have become increasingly common in epidemiology and public health research thanks to advances in GIS (Geographic Information Systems) technology. In health research, for example, it is common for epidemiologists to incorporate geographically indexed data into their studies. In practice, however, the spatially defined
Huque, MH +3 more
openaire +4 more sources