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Primary-Auxiliary Statistical Local Kernel Principal Component Analysis and Its Application to Incipient Fault Detection of Nonlinear Industrial Processes

机译：主要辅助统计本地内核主成分分析及其在非线性工业过程中初期故障检测的应用

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Xiaogang Deng; Peipei Cai; Jiawei Deng; Yuping Cao; Zhihuan Song;
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年度 2019
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2. Multi-block statistics local kernel principal component analysis algorithm and its application in nonlinear process fault detection [J] . Neurocomputing . 2020,第Feba1期

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3. Modified kernel principal component analysis based on local structure analysis and its application to nonlinear process fault diagnosis [J] . Xiaogang Deng, Xuemin Tian, Sheng Chen Chemometrics and Intelligent Laboratory Systems . 2013,第Null期

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4. Statistics kernel principal component analysis for nonlinear process fault detection [C] . Ma Hehe, Hu Yi, Shi Hongbo 2011 9th World Congress on Intelligent Control and Automation : Conference Digest . 2011

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5. Statistical monitoring and fault diagnosing of multivariate processes based on nonlinear principal component analysis. [D] . Li, Xueman. 2004

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6. Between Nonlinearities Complexity and Noises: An Application on Portfolio Selection Using Kernel Principal Component Analysis [O] . Yaohao Peng, Pedro Henrique Melo Albuquerque, Igor Ferreira do Nascimento, 2019

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Primary-Auxiliary Statistical Local Kernel Principal Component Analysis and Its Application to Incipient Fault Detection of Nonlinear Industrial Processes

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