Modified kernel regression method for the denoising of X-ray pulsar profiles
Sign Up to like & getrecommendations! Published in 2018 at "Advances in Space Research"
DOI: 10.1016/j.asr.2018.04.027
Abstract: Abstract In this paper, a modified kernel regression algorithm is proposed to reduce the noise of pulsar profiles autonomously. Taking advantage of the classical autonomous kernel regression the presented algorithm based on the second-order derivative… read more here.
Keywords: pulsar profiles; kernel regression; regression; modified kernel ... See more keywords
Fault Detection Based on Modified Kernel Semi-Supervised Locally Linear Embedding
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2017.2767698
Abstract: In this paper, a novel approach to fault detection for nonlinear processes is proposed. It is based on a manifold learning called modified kernel semi-supervised local linear embedding. Local linear embedding (LLE) is widely applied… read more here.
Keywords: fault detection; linear embedding; modified kernel; semi supervised ... See more keywords
Optimal error bound and modified kernel method for a space-fractional backward diffusion problem
Sign Up to like & getrecommendations! Published in 2018 at "Advances in Difference Equations"
DOI: 10.1186/s13662-018-1728-2
Abstract: In this paper, we consider a backward problem for a space-fractional diffusion equation. This problem is ill-posed, i.e., the solution does not depend continuously on the data. The optimal error bound for the problem under… read more here.
Keywords: backward; space fractional; modified kernel; optimal error ... See more keywords