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Pattern Recognition, ISSN 0031-3203, 2007, Volume 40, Issue 3, pp. 863 - 874
Kernel principal component analysis (kernel PCA) is a non-linear extension of PCA. This study introduces and investigates the use of kernel PCA for novelty... 
Breast cancer | Novelty detection | Handwritten digit | Kernel method | PCA | novelty detection | kernel method | handwritten digit | breast cancer | CLASSIFICATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
IEEE Transactions on Fuzzy Systems, ISSN 1063-6706, 02/2010, Volume 18, Issue 1, pp. 67 - 79
Journal Article
Neural Networks, ISSN 0893-6080, 2009, Volume 22, Issue 5, pp. 642 - 650
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 01/2004, Volume 26, Issue 1, pp. 131 - 137
In this paper, a new technique coined two-dimensional principal component analysis (2DPCA) is developed for image representation. As opposed to PCA, 2DPCA is... 
Image databases | Face recognition | Lighting | Independent component analysis | Image representation | Feature extraction | Covariance matrix | Face detection | Kernel | Principal component analysis | Eigenfaces | Principal Component Analysis (PCA)
Journal Article
Control Engineering Practice, ISSN 0967-0661, 01/2014, Volume 22, Issue 1, pp. 205 - 216
In this paper, a novel approach for processes monitoring, termed as filtering kernel independent component analysis–principal component analysis (FKICA–PCA),... 
Process monitoring | Variance of independent component | KICA–PCA | Variable contribution analysis | TE process | EWMA | KICA-PCA | KPCA | DIAGNOSIS | ALGORITHMS | INDEPENDENT COMPONENT ANALYSIS | ENGINEERING, ELECTRICAL & ELECTRONIC | FAULT-DETECTION | AUTOMATION & CONTROL SYSTEMS | Analysis | Algorithms | Kernels | Filtration | Filtering | Mathematical analysis | Nonlinearity | Feasibility | Gaussian | Monitoring
Journal Article
Chemical Engineering Science, ISSN 0009-2509, 2009, Volume 64, Issue 9, pp. 2245 - 2255
Conventional kernel principal component analysis (KPCA) may not function well for nonlinear processes, since the Gaussian assumption of the method may be... 
System engineering | Statistical local approach | Safety | Kernel principal component analysis | Process control | Nonlinear dynamic | LOCAL APPROACH | ENGINEERING, CHEMICAL | FAULT IDENTIFICATION | BATCH PROCESSES | NEURAL-NETWORKS | PRINCIPAL COMPONENT ANALYSIS | Control systems | Analysis | Production processes
Journal Article
Industrial and Engineering Chemistry Research, ISSN 0888-5885, 03/2007, Volume 46, Issue 7, pp. 2054 - 2063
Many of the current multivariate statistical process monitoring techniques (such as principal component analysis (PCA) or partial least squares (PLS)) do not... 
ENGINEERING, CHEMICAL | DIAGNOSIS | BATCH PROCESSES | DISTURBANCES | MULTIVARIATE | FAULT-DETECTION | MULTIPLE OPERATING MODES | HISTORICAL DATA | KERNEL DENSITY-ESTIMATION | CHARTS
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 3/2019, pp. 1 - 1
We present an algorithm for L1-norm kernel PCA and provide a convergence analysis for it. While an optimal solution of L2-norm kernel PCA can be obtained... 
L1-norm | Loading | Outlier Detection | Matrix decomposition | Sparse matrices | Kernel | Anomaly detection | Principal component analysis | Convergence
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 05/2004, Volume 26, Issue 5, pp. 572 - 581
Journal Article
IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 01/2012, Volume 23, Issue 1, pp. 163 - 168
Journal Article
Pattern Recognition Letters, ISSN 0167-8655, 11/2014, Volume 49, pp. 114 - 120
Kernel Principal Component Analysis (PCA) has proven a powerful tool for nonlinear feature extraction, and is often applied as a pre-processing step for... 
Kernel PCA | Semi-supervised denoising | Pre-image problem | EIGENVALUE PROBLEM | PRE-IMAGES | COMPONENT ANALYSIS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
International Journal of Quantum Information, ISSN 0219-7499, 12/2018, Volume 16, Issue 8
In many-body physics, renormalization techniques are used to extract aspects of a statistical or quantum state that are relevant at large scale, or for low... 
kernel PCA | Bayesian inference | machine learning | Quantum field theory | fisher information metric | COMPUTER SCIENCE, THEORY & METHODS | PHYSICS, MATHEMATICAL | PHYSICS, PARTICLES & FIELDS
Journal Article
Journal of Computational Physics, ISSN 0021-9991, 10/2016, Volume 322, pp. 859 - 881
Journal Article
IAENG International Journal of Computer Science, ISSN 1819-656X, 02/2016, Volume 43, Issue 1, pp. 72 - 79
The network traffic data used to build an intrusion detection system is frequently enormous and redundant with important useless information which decreases... 
Kpca | Network security | Intrusion detection system (ids) | Pca | Kernels | Classifiers | Networks | Intrusion | Denial of service attacks | Decision trees | Computer information security | Principal component analysis
Journal Article
International Journal of Computational Science and Engineering, ISSN 1742-7185, 2018, Volume 16, Issue 1, pp. 9 - 16
In the last years, the problem of detecting anomalies and attacks by statistically inspecting the network traffic has been attracting more and more research... 
kernel-PCA | network anomaly detection | intrusion detection system | Performance enhancement | Denial of service attacks | Communications traffic | Computer security | Anomalies
Journal Article
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