Results 71 to 80 of about 623,991 (302)

Do unbalanced data have a negative effect on LDA? [PDF]

open access: yes, 2008
For two-class discrimination, Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562] claimed that, when covariance matrices of the two classes were unequal, a (class ...
Titterington, D.M., Xue, J.H.
core   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational 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   +3 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

open access: yesAdvanced 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

Invariant Tests on Covariance Matrices

open access: yesThe Annals of Statistics, 1981
Minimal complete classes of invariant tests are presented for modifications of the problem of testing the independence of $Y$ and $X$, where $(Y, X) \equiv (Y, X_1, \cdots, X_p)$ is a multivariate normal random vector. One modification involves having extra independent observations on $Y$.
openaire   +2 more sources

An Epigenetic Fate Converter Based on Nuclei‐Targeting Lipid Nanoparticles Drives Neuronal Programming of Stem Cells for Spinal Cord Repair

open access: yesAdvanced Functional Materials, EarlyView.
Schematic illustration of LNP‐MPG nuclei‐targeting delivery of HMW‐FGF2 promoting histone acetylation to regulate the fate of DPSCs and treat spinal cord injury. LNPs components include pHMW‐FGF2 plasmid, DSPC, Dlin‐MC3‐DMA, cholesterol, and PEG2000, and are modified with MPG to form HMW‐FGF2@LNP‐MPG (HLM). HLM nuclei‐targets DPSCs to deliver HMW‐FGF2,
Heng Zhou   +6 more
wiley   +1 more source

Pose estimation by extended Kalman filter using noise covariance matrices based on sensor output

open access: yesROBOMECH Journal, 2020
This paper presents an extended Kalman filter for pose estimation using noise covariance matrices based on sensor output. Compact and lightweight nine-axis motion sensors are used for motion analysis in widely various fields such as medical welfare and ...
Ayuko Saito   +3 more
doaj   +1 more source

Full‐Field Damage Monitoring in Architected Lattices Using In situ Electrical Impedance Tomography

open access: yesAdvanced Functional Materials, EarlyView.
In situ electrical impedance tomography (EIT) turns 3D‐printed, CNT‐infused architected lattices into full‐field damage‐imaging systems. Tunable Voronoi‐based geometries act as active sensing architectures, enabling conductivity maps to detect early‐stage damage and localise sequential ligament fracture before catastrophic failure.
Akash Deep   +4 more
wiley   +1 more source

Radar Target Detection Method of Aircraft Wake Vortices Based on Matrix Information Geometry

open access: yesLeida xuebao, 2017
The application of matrix information geometry to radar signal processing and target detection is a new and interesting subject. Wake vortices are Doppler-spread after Fourier transform.
Liu Junkai   +4 more
doaj   +1 more source

Separable Covariance Matrices and Kronecker Approximation

open access: yesProcedia Computer Science, 2017
Abstract When a model structure allows for the error covariance matrix to be written in the form of the Kronecker product of two positive definite covariance matrices, the estimation of the relevant parameters is intuitive and easy to carry out. In many time series models, the covariance matrix does not have a separable structure.
Raja Velu, Kris Herman
openaire   +1 more source

Covariance matrices for experimental stimuli.

open access: yes, 2016
Covariance matrices for experimental stimuli.
Christian E. Stilp (334561)   +1 more
core   +1 more source

Home - About - Disclaimer - Privacy