Results 71 to 80 of about 260,346 (290)
ANALISIS GRAFIK PENGENDALI NONPARAMETRIK DENGAN ESTIMASI FUNGSI DENSITAS KERNEL PADA KASUS WAKTU PELOROTAN BATIK TULIS [PDF]
, 2013 The quality of the product becomes one of the basic factors in the decisions of consumers in selecting products. A companny needs a quality control for keeping the consistency of product quality.
HAYATI, HANA
core
Advanced Materials, EarlyView.Triply‐twinned architected lattices transform deformation from bending to stretching of struts, delivering up to threefold increases in stiffness and strength across polymeric and metallic systems. High‐resolution synchrotron XCT and image‐based simulations reveal how meta‐grain architecture, defects, and AM build orientation govern failure pathways ...
David McArthur +7 more
wiley +1 more source
Nonparametric methods for volatility density estimation
, 2009 Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process.
Spreij, Peter +2 more
core
Local Component Analysis [PDF]
, 2011 Kernel density estimation, a.k.a. Parzen windows, is a popular density estimation method, which can be used for outlier detection or clustering. With multivariate data, its performance is heavily reliant on the metric used within the kernel. Most earlier
Bach, Francis, Roux, Nicolas Le
core +5 more sources
Advanced Materials, EarlyView.A fully flexible ion‐gel‐gated graphene‐channel transistor driven by a triboelectric nanogenerator enables self‐powered tactile sensing and synaptic learning. Mimicking spike‐rate‐dependent plasticity, the device exhibits frequency‐selective potentiation and depression, supporting rate‐coded neuromorphic computation even under flex.
Hanseong Cho +3 more
wiley +1 more source
A Novel Flexible Kernel Density Estimator for Multimodal Probability Density Functions
CAAI Transactions on Intelligence TechnologyEstimating probability density functions (PDFs) is critical in data analysis, particularly for complex multimodal distributions. traditional kernel density estimator (KDE) methods often face challenges in accurately capturing multimodal structures due to
Jia‐Qi Chen +5 more
doaj +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
doaj +1 more source
Alternating kernel and mixture density estimates
Computational Statistics & Data Analysis, 2000 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Priebe, C. E., Marchette, D. J.
openaire +2 more sources
Superionic Amorphous Li2ZrCl6 and Li2HfCl6
Advanced Materials, EarlyView.Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley +1 more source
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
doaj +1 more source