Results 71 to 80 of about 4,584 (156)
IEEE Access, 2017 Kernel principal component analysis (KPCA) has been a state-of-the-art nonlinear process monitoring method. However, KPCA assumes the single operation mode while the real industrial processes often run under multiple operation conditions.
Xiaogang Deng, Na Zhong, Lei Wang
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Kernelized design of experiments [PDF]
This paper describes an approach for selecting instances in regression problems in the cases where observations x are readily available, but obtaining labels y is hard.
Rüping, Stefan, Weihs, Claus
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Acoustic analysis assessment in speech pathology detection
International Journal of Applied Mathematics and Computer Science, 2015 Automatic detection of voice pathologies enables non-invasive, low cost and objective assessments of the presence of disorders, as well as accelerating and improving the process of diagnosis and clinical treatment given to patients.
Panek Daria +3 more
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IEEE AccessPregnancy complications significantly impact maternal and fetal health, requiring accurate and timely diagnostic methods for life-saving interventions.
Ariana Deyaneira Jimenez-Narvaez +6 more
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kernlab - An S4 Package for Kernel Methods in R [PDF]
kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 ob ject model and provides a framework for creating and using kernel-based algorithms. The package contains dot product primitives (kernels),
Achim Zeileis +3 more
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Research on indoor localization algorithm based on kernel principal component analysis
Tongxin xuebao, 2017 An indoor localization algorithm based on kernel principal component analysis (KPCA) was proposed.It applied KPCA to train the original location fingerprint (OLF) and extract the nonlinear feature of the OLF data at the offline stage,such that the ...
Hua-liang LI +2 more
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Fault diagnosis method of train control RBC system based on KPCA-SOM network
Journal of Measurement Science and Instrumentation, 2020 Radio block center（RBC） system is the core equipment of China train control system-3（CTCS-3）. Now, the fault analysis of RBC system mainly depends on manual work, and the diagnostic results are inaccurate and inefficient. Therefore, the intelligent fault
LI Yang-qing, LIN Hai-xiang
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IEEE AccessFault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA).
Mohammed Tahar Habib Kaib +4 more
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Jixie qiangdu, 2016 Grouplet transform is a new directional wavelet. This wavelet can be transformed at any time and space,and adaptively change the basis according to image texture.
LI ZhiNong +3 more
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