Nonlinear machine fault detection by semi-supervised Laplacian Eigenmaps
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Mechanical Science and Technology"
DOI: 10.1007/s12206-017-0712-1
Abstract: A semi-supervised Laplacian Eigenmaps algorithm for machine fault detection is proposed. The purpose of the algorithm is to efficiently extract the manifold geometric characteristics of nonlinear vibration signal samples, and to determine fault classification of… read more here.
Keywords: fault; semi supervised; fault detection; laplacian eigenmaps ... See more keywords
Characterizing the transient electrocardiographic signature of ischemic stress using Laplacian Eigenmaps for dimensionality reduction
Sign Up to like & getrecommendations! Published in 2020 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2020.104059
Abstract: OBJECTIVE Despite a long history of ECG-based monitoring of acute ischemia quantified by several widely used clinical markers, the diagnostic performance of these metrics is not yet satisfactory, motivating a data-driven approach to leverage underutilized… read more here.
Keywords: laplacian eigenmaps; ischemia; dimensionality reduction; performance ... See more keywords
A dimensionality reduction method of continuous dependent variables based supervised Laplacian eigenmaps
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2019.1607347
Abstract: ABSTRACT Dimensionality reduction is one of the important preprocessing steps in high-dimensional data analysis. In this paper we propose a supervised manifold learning method, it makes use of the information of continuous dependent variables to… read more here.
Keywords: continuous dependent; dependent variables; dimensionality reduction; laplacian eigenmaps ... See more keywords
Effective Dimensionality Reduction for Visualizing Neural Dynamics by Laplacian Eigenmaps
Sign Up to like & getrecommendations! Published in 2019 at "Neural Computation"
DOI: 10.1162/neco_a_01203
Abstract: With the development of neural recording technology, it has become possible to collect activities from hundreds or even thousands of neurons simultaneously. Visualization of neural population dynamics can help neuroscientists analyze large-scale neural activities efficiently.… read more here.
Keywords: reduction visualizing; neural dynamics; laplacian eigenmaps; visualizing neural ... See more keywords