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1.Kernel-based methods for source identification using very small particles from carpet fibers

作者：D.E. Armstrong^a ; C. Neumann^a ; ^{Cedric.Neumann@me.com} ; C.P. Saunders^a ; D.T. Gantz^b ; J.J. Miller^c ; D.A. Stoney^d

关键词：Very small particles ; Kernel based-methods ; High-dimensional classification ; Closed-set identification

刊名：Chemometrics and Intelligent Laboratory Systems

出版年：2017

2.Pulsar profile denoising using kernel regression based on maximum correntropy criterion

作者：Yidi Wang ; ^{wangyidi19860609@163.com} ; Wei Zheng ; Dapeng Zhang ; Lu Zhang

关键词：X-ray pulsar-based navigation ; Kernel regression ; Correntropy

刊名：Optik - International Journal for Light and Electron Optics

出版年：2017

3.Kernel-based dimensionality reduction using Renyi's α-entropy measures of similarity

作者：A.M. Alvarez-Meza^a ; ^{amalvarezme@unal.edu.co}Author Vitae ; J.A. Lee^b ; ^{john.lee@uclouvain.be}Author Vitae ; Michel Verleysen^b ; ^{michel.verleysen@uclouvain.be}Author Vitae ; G. Castellanos-Dominguez^a ; ^{cgcastellanosd@unal.edu.co}Author Vitae

关键词：Dimensionality reduction ; Kernel methods ; Renyi's α-entropy

刊名：Neurocomputing

出版年：2017

4.3D MR image denoising using rough set and kernel PCA method

作者：Ashish Phophalia^a ; ^{ashish_p@iiitvadodara.ac.in} ; Suman K. Mitra^b ; ^{suman_mitra@daiict.ac.in} ;

关键词：Image denoising ; Magnetic resonance imaging ; Rough set theory ; Kernel Principle Component Analysis

刊名：Magnetic Resonance Imaging

出版年：2017

5.In search of an optimal kernel for a bias correction method for density estimators

作者：Lyudmila Sakhanenko ^{luda@stt.msu.edu}

关键词：Kernel smoothing ; Integrated mean square error ; Density estimation

刊名：Statistics & Probability Letters

出版年：2017

6.A spectral-spatial kernel-based method for hyperspectral imagery classification

作者：Li Li^a ; ^{lili.jnu@gmail.com} ; ^{liliiot@163.com} ; Hongwei Ge^a ; ^{ghw8601@163.com} ; Jianqiang Gao^b ; ^{dr.jq.gao@gmail.com} ; ^{jianqianggaohh@126.com}

关键词：Hyperspectral imagery classification (HIC) ; Area median filtering (AMF) ; Spectral-spatial kernel (SSK) ; Support vector machine (SVM)

刊名：Advances in Space Research

出版年：2017

7.Numeric solution of Volterra integral equations of the first kind with discontinuous kernels

作者：Ildar Muftahov^a ; Aleksandr Tynda^b ; Denis Sidorov^a ; ^c ; ^{contact.dns@gmail.com" class="auth_mail" title="E-mail the corresponding author}

关键词：Volterra integral equations ; Discontinuous kernels ; Direct quadrature method ; Regularization ; Evolving dynamical systems ; Midpoint quadrature

刊名：Journal of Computational and Applied Mathematics

出版年：2017

8.Application of alternative synthetic kernel approximation to radiative transfer in regular and irregular two-dimensional media

作者：Zekeriya Altaç ; ; ¹ ; ^{zaltac@ogu.edu.tr} ; ^{zbocu@ogu.edu.tr} ; Zerrin Sert

关键词：Synthetic kernel ; Irregular medium ; Radiative transfer ; Participating medium ; Alternative

刊名：Journal of Quantitative Spectroscopy and Radiative Transfer

出版年：2017

9.Composite kernel support vector machine based performance enhancement of brain computer interface in conjunction with spatial filter

作者：Jyoti Singh Kirar ; ^{kirarjyoti@gmail.com} ; ^{kirarjyoti@gmail.com} ; R.K. Agrawal ^{rkajnu@gmail.com}

关键词：Brain computer interface ; Composite kernels ; Common spatial patterns ; Recursive feature elimination ; Support vector machine ; Motor imagery

刊名：Biomedical Signal Processing and Control

出版年：2017

10.Feature selection and multiple kernel boosting framework based on PSO with mutation mechanism for hyperspectral classification

作者：Chengming Qi^a ; ^b ; ^{chming.qi@gmail.com}Author Vitae ; Zhangbing Zhou^a ; ^c ; ^{zhangbing.zhou@gmail.com}Author Vitae ; Yunchuan Sun^dAuthor Vitae ; Houbing Song^e ; ^{Houbing.Song@mail.wvu.edu}Author Vitae ; Lishuan Hu^a ; ^b ; ^{hulishuan@163.com}Author Vitae ; Qun Wang^a ; ^{qunw@cugb.edu.cn}Author Vitae

关键词：Ensemble learning ; Feature selection ; Hyperspectral remote sensing image ; Multiple kernel boosting

刊名：Neurocomputing

出版年：2017

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