EurekAlert!

Teaching neural networks where errors matter

Physics-informed neural networks (PINNs) have shown remarkable prospects in solving forward and inverse problems involving ...
IEEE

Enhanced Kernel Density Estimation via Gram-Charlier series for Accurate Fault Modeling in Electrical Connectors

Abstract: Kernel density estimation (KDE), a flexible nonparametric technique unconstrained by specific data distribution assumptions, is extensively employed in fault modeling. However, its ...
IEEE

Kernel Density Estimation and Bayesian Network to Represent Correlation of Variable Generation and Load in the State-Space Sampling Technique

Abstract: This paper explores a method for preserving correlations between random variables in the state-space sampling technique that is adopted in Non-Sequential Monte Carlo Simulation. The proposed ...
GitHub

Baseline_Wander_estimation.m

% H = Baseline_Wander_estimation returns the handle to a new Baseline_Wander_estimation or the handle to % the existing singleton*. % Baseline_Wander_estimation('CALLBACK',hObject,eventData,handles,..