Results 61 to 70 of about 49,315 (263)
A Kernel-Based Calculation of Information on a Metric Space
Entropy, 2013 Kernel density estimation is a technique for approximating probability distributions. Here, it is applied to the calculation of mutual information on a metric space.
Conor J. Houghton, R. Joshua Tobin
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Choice of Kernel Order in Density Estimation
The Annals of Statistics, 1988 The selection of the order, i.e. number of vanishing moments, of the kernel in a kernel density estimator is considered from two points of view. First, theoretical properties are investigated by a mean integrated squared error analysis of the problem.
Hall, Peter, Marron, J. S.
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Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Advanced Engineering Materials, EarlyView.Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
Acta Universitatis Lodziensis. Folia Oeconomica, 2017 Ad hoc methods in the choice of smoothing parameter in kernel density estimation, although often used in practice due to their simplicity and hence the calculated efficiency, are characterized by quite big error.
Aleksandra Katarzyna Baszczyńska
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Advanced Functional Materials, EarlyView.ABSTRACT Chitosan, a polysaccharide upcycled from biowaste, has long promised sustainable, biocompatible, and antimicrobial films and devices, an appeal reinforced by its recent regulatory recognition, with several chitosan‐based antibacterial dressings gaining clearance through the Food and Drug Administration's 510(k) pathway.
Jacopo Nicoletti +16 more
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Heuristic Kernel Density Estimator for Modal‑Proximity Data
Shuju Caiji Yu ChuliDifferent from the classical probability density estimator construction strategies based on the Parzen window method， we propose a heuristic kernel density estimator （HKDE） based on nearest neighbor error measurement function， to improve the accuracy of ...
HE Yulin +4 more
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Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing
Advanced Functional Materials, EarlyView.A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin +7 more
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Enhancing Broiler Weight Estimation through Gaussian Kernel Density Estimation Modeling
AgricultureThe management of individual weights in broiler farming is not only crucial for increasing farm income but also directly linked to the revenue growth of integrated broiler companies, necessitating prompt resolution.
Yumi Oh +4 more
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Geometric Inference on Kernel Density Estimates
CoRR, 2013 To appear in SoCG 2015.
Jeff M. Phillips +2 more
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Advanced Functional Materials, EarlyView.Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu +12 more
wiley +1 more source