Results 111 to 120 of about 7,040 (158)
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KPCA Plus FDA for Fault Detection
2007Kernel principal component analysis (KPCA) is widely used for fault detection. In this paper, a KPCA plus Fisher discriminant analysis (FDA) scheme is adopted to improve the fault detection performance of KPCA. Simulation results are given to show the effectiveness of the improvements for fault detection performance in terms of high fault detection ...
Peiling Cui, Jiancheng Fang
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Greedy KPCA in Biomedical Signal Processing
2007Biomedical signals are generally contaminated with artifacts and noise. In case artifacts dominate, the useful signal can easily be extracted with projective subspace techniques. Then, biomedical signals which often represent one dimensional time series, need to be transformed to multi-dimensional signal vectors for the latter techniques to be ...
Ana R. Teixeira +2 more
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A hybrid BGWO with KPCA for intrusion detection
Journal of Experimental & Theoretical Artificial Intelligence, 2019Intrusion detection is the primary model for giving security to the network. There are numerous issues with conventional intrusion detection models (for example, low detection ability against obscu...
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Stellar Parameterisation using KPCA and SVM
Proceedings of the International Astronomical Union, 2017AbstractWith so many spectroscopic surveys, both past and upcoming, such as SDSS and LAMOST, the number of accessible stellar spectra is continuously increasing. There is therefore a great need for automated procedures that will derive estimates of stellar parameters. Working with spectra from SDSS and LAMOST, we put forward a hybrid approach of Kernel
H. Yuan +8 more
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Combining KPCA and PSO for Pattern Denoising
2008 Chinese Conference on Pattern Recognition, 2008KPCA based pattern denoising has been addressed. This method, based on machine learning, maps nonlinearly patterns in input space into a higher-dimensional feature space by kernel functions, then performs PCA in feature space to realize pattern denoising.
Jianwu Li, Lu Su
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An application of KPCA in the human face recognition
Proceedings of 2013 2nd International Conference on Measurement, Information and Control, 2013A face recognition method that based on KPCA and SVM is proposed in this paper. In the method, an SVM support vector machine is employed to process a small-sample-size problem and KPCA kernel principal component analysis is applied to deal with a high order statistics of original data, and to describe the correlation among multiple pixels in an image.
null Meng Qing Song, null Yuan Hai Bo
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KPCA Feature Extraction Based on CBPSO
2009 International Workshop on Intelligent Systems and Applications, 2009How to choose the best or near kernel function to reduce test error rate is the key of KPCA applied to extract nonlinear feature. In this article, on the basis of research of CA, PSO, we propose a programmer flow of CBPSO used for training kernel function and build CBPSO-KPCA. This approach can effectively optimize kernel function.
Zhao Min +3 more
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Facial expression analysis by using KPCA
IEEE International Conference on Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003, 2004This paper discussed a problem of robustness of existing kernel principal component analysis (KPCA) and proposed a new approach to do facial expression analysis by using KPCA. Experimental results on CMU facial expression image database and Yale database are encouraging.
null Zhong Jin +2 more
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Manifold based kernel optimization for KPCA
2011 IEEE 3rd International Conference on Communication Software and Networks, 2011This paper presents a manifold based kernel optimizing algorithm for KPCA which has recently shown effectiveness for pattern recognition and systematic classification based on extracting nonlinear features. However, their performances largely depend on the kernel function.
Li Zeng, Bin Chen, Linping Du, Kejia Xu
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PCA and KPCA of ECG signals with binary SVM classification
2011 IEEE Workshop on Signal Processing Systems (SiPS), 2011Cardiac problems are the main reason of people's death nowadays. However, one way that light save the life is the analysis of the an electrocardiograph. This analysis consist in the diagnosis of the arrhythmia when it presents. In this paper, we propose to combine the Support Vector Machines used in classification on one hand, with the Principal ...
Kanaan, Lara +5 more
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