Results 81 to 90 of about 534,560 (282)

Recursive Bayesian Initialization of Localization Based on Ranging and Dead Reckoning

open access: yes, 2013
The initialization of the state estimation in a localization scenario based on ranging and dead reckoning is studied. Specifically, we start with a cooperative localization setup and consider the problem of recursively arriving at a uni-modal state ...
Händel, Peter, Nilsson, John-Olof
core   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

open access: yesAdvanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell   +3 more
wiley   +1 more source

Shrinkage Algorithms for MMSE Covariance Estimation

open access: yes, 2009
We address covariance estimation in the sense of minimum mean-squared error (MMSE) for Gaussian samples. Specifically, we consider shrinkage methods which are suitable for high dimensional problems with a small number of samples (large p small n). First,
Alfred O. Hero   +5 more
core   +2 more sources

Local Covariance Estimation Using Costationarity [PDF]

open access: yes, 2014
In this paper we propose a novel estimator for the time-varying covariance of locally stationary time series. This new approach is based on costationary combinations, that is, time-varying deterministic combinations of locally stationary time series that are second-order stationary.
openaire   +2 more sources

Multimodal Data‐Driven Microstructure Characterization

open access: yesAdvanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang   +4 more
wiley   +1 more source

High‐Temperature Nanoindentation of Metals: Assessing Thermal Drift, Frame Compliance, and Chemical Composition Effects on the Reported Mechanical Properties

open access: yesAdvanced Engineering Materials, EarlyView.
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova   +2 more
wiley   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

open access: yesAdvanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi   +2 more
wiley   +1 more source

Regularization for high-dimensional covariance matrix

open access: yesSpecial Matrices, 2016
In many applications, high-dimensional problem may occur often for various reasons, for example, when the number of variables under consideration is much bigger than the sample size, i.e., p >> n.
Cui Xiangzhao   +5 more
doaj   +1 more source

Geometric methods for estimation of structured covariances [PDF]

open access: yes, 2011
We consider problems of estimation of structured covariance matrices, and in particular of matrices with a Toeplitz structure. We follow a geometric viewpoint that is based on some suitable notion of distance. To this end, we overview and compare several
Georgiou, Tryphon   +2 more
core   +1 more source

BACH, a Bayesian Optimization Protocol for Accurate Coarse‐Grained Parameterization of Organic Liquids

open access: yesAdvanced Functional Materials, EarlyView.
We present a fully automated Bayesian optimization (BO) protocol for the parameterization of nonbonded interactions in coarse‐grain CG force fields (BACH). Using experimental thermophysical data, we apply the protocol to a broad range of liquids, spanning linear, branched, and unsaturated hydrocarbons, esters, triglycerides, and water.
Janak Prabhu   +3 more
wiley   +1 more source

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