Results 51 to 60 of about 192,804 (181)
Kernel Mean Shrinkage Estimators [PDF]
, 2016 A mean function in a reproducing kernel Hilbert space (RKHS), or a kernel mean, is central to kernel methods in that it is used by many classical algorithms such as kernel principal component analysis, and it also forms the core inference step of modern ...
Fukumizu, Kenji +4 more
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Shanghai Jiaotong Daxue xuebao, 2020 It is difficult to accurately measure parameters by using the traditional soft sensor algorithm when the working condition of industrial process is changed. Therefore, a transfer learning strategy is introduced based on geodesic flow kernel to solve this
LAI Yanbo +3 more
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IEEE Access, 2021 Single traditional multivariate statistical monitoring methods, such as principal component analysis (PCA) and canonical variate analysis (CVA), are less effective in nonlinear dynamic processes.
Liangliang Shang +4 more
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Face Recognition Using Kernel Principal Component Analysis
, 2014 Face recognition is attracting much attention in the society of network multimedia information access. Areas such as network security, content indexing and retrieval, and video compression benefits from face recognition technology because people are the center of attention in a lot of video.
T, Jayanthi, Aji S
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Tikrit Journal of Pure Science, 2018 In recent year, Face recognition system has taken much attention and used for different types of purposes for instance web application authentication, online investment and banking, mobile authentication, smart home security, virtual reality, database ...
Harith A. Hussein
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Gene Expression Data Classification With Kernel Principal Component Analysis [PDF]
BioMed Research International, 2005 One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. Development of new methodologies or modification of existing methodologies is needed for the analysis of the microarray data.
Liu, Zhenqiu +2 more
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High Quality Microblog Extraction Based on Kernel Principal Component Analysis and Wavelet Transformation [PDF]
Jisuanji gongcheng, 2016 Massive social event relevant messages are generated in online social media,which makes the filtering and screening of them be a challenge.In order to obtain massages with high quality,a high quality information extraction framework based on Kernel ...
PENG Min,FU Hui,HUANG Jimin,HUANG Jiajia,LIU Jiping
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Advances in Mechanical Engineering, 2016 To effectively extract the typical features of the bearing, a new method that related the local mean decomposition Shannon entropy and improved kernel principal component analysis model was proposed.
Jinlu Sheng +3 more
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Analysis of heat kernel highlights the strongly modular and heat-preserving structure of proteins
, 2015 In this paper, we study the structure and dynamical properties of protein contact networks with respect to other biological networks, together with simulated archetypal models acting as probes.
Giuliani, Alessandro +5 more
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IEEE Access, 2020 In order to guarantee and improve the product quality, the data-driven fault detection technique has been widely used in industry. For three-way datasets of batch process in industry process (i.e., batch × variable × time), a novel method ...
Fei He, Zhiyan Zhang
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