[PDF] Top 20 Fast Iterative Kernel Principal Component Analysis
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Fast Iterative Kernel Principal Component Analysis
... the kernel Hebbian algorithm (KHA) for iterative kernel PCA (Kim et ...reproducing kernel Hilbert space to further speed up ...on kernel PCA and spectral clustering of USPS digits, ... See full document
26
A Novel Intrusion Detection System Based On Kpca And Rvm With Pso Model
... parameter, Kernel principal component analysis method is used to reduce ...the kernel principal component analysis method can extract nonlinear ... See full document
8
Detecting abnormality in optic nerve head images using a feature extraction analysis
... and kernel principal component analysis to quantify the shape features in ONH images acquired by scanning laser ophthalmoscopy (Heidelberg Retina Tomograph ...ROC analysis, was ... See full document
17
Principal component analysis for fast and automated thermographic inspection of internal structures in sandwich parts
... reinforced plastic. These inserts replace the honeycomb core to absorb stresses in a defined way (Bitzer, 1997). Quality in- spection requires controlling these inserts for presence, cor- rect type, and deviation of ... See full document
7
Euler principal component analysis
... liers. In this paper, we propose a kernel PCA method for fast and robust PCA, which we call Euler-PCA (e-PCA). In particular, our algorithm utilizes a robust dissimilarity measure based on the Euler ... See full document
21
Inference on point processes with unobserved one dimensional reference structure
... a Principal Component Analysis ...first principal component then can be used as an orientation estimate for the anisotropic point ...a kernel-based Principle Component ... See full document
12
The Prediction Model of Financial Crisis Based on the Combination of Principle Component Analysis and Support Vector Machine
... of principal component analysis (PCA) and Support Vector Machine (SVM) to predict financial ...the kernel function is polynomial, and the prediction accuracy of the combination model is ... See full document
9
Kernel Principal Component Analysis for the Classification of Hyperspectral Remote Sensing Data over Urban Areas
... A nonlinear version of the PCA has been shown to be capable of capturing a part of higher-order statistics, thus better representing the information from the original data set [19, 20]. The first objective of this ... See full document
14
MRI BRAIN IMAGE CLASSIFICATION USING POLYNOMIAL KERNEL PRINCIPAL COMPONENT ANALYSIS WITH NEURAL NETWORK
... This work proposed the efficient method for detection of normal or abnormal brain images. Various classification rates are obtained using different power of applied kernel. Confusion matrix obtained by ... See full document
8
Application of LSSVM to logistics demand forecasting based on grey relational analysis and kernel principal component analysis
... nonlinear principal components as inputs. The forecasting performance of the GRA-KPCA-LSSVM model is investigated through the use of China logistics data. The results show that the GRA-KPCA-LSSVM model has ... See full document
6
Facial Landmark Detection and Localisation using Explicit Model Based Approach
... like Component based Deformable Model, Constrained Local Model (CLM) and Parameterized Kernel Principal Component Analysis (PKPCA) are not robust to pose variations, expressions on face ... See full document
8
Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis
... motion analysis that requires no physical contact has become a popular solution for gait analysis ...gait analysis for precise data collection, reliable quantitative measurements, and systematic data ... See full document
21
A New Approach for Iris and Fingerprint Recognition based on KPCA and LLE Algorithm
... using kernel principal component analysis (KPCA) and fingerprint can be recognized using locally linear embedding (LLE), is proposed ... See full document
5
Comparison Study of Partial Least Squares Regression Analysis and Principal Component Analysis in Fast-Scan Cyclic Voltammetry
... FSCV analysis once, to the best of our knowledge ...an analysis of cyclic voltammograms is underlined by the fact that the prediction of unknown cyclic voltammograms is based on the causal relationship ... See full document
14
Chemometric Feature Selection and Classification of Ganoderma lucidum Spores and Fruiting Body Using ATR FTIR Spectroscopy
... and fast discrimination of raw materials of Chinese herbal ...discriminant analysis, principal component discriminant analysis and partial least squares discriminant analy- sis has been ... See full document
11
A Data Driven Statistical Approach for Monitoring and Analysis of Large Industrial Processes
... the principal component analysis (PCA) method and the associated probability density ...statistical analysis of the ...Function, Principal Component Analysis, ... See full document
6
OPTIMIZATION OF HIGH VOLTAGE POWER SUPPLY FOR INDUSTRIAL MICROWAVE GENERATORS FOR ONE MAGNETRON
... Principal component analysis (PCA) is a standard linear transformation technique that reduces the number of data dimensions without much loss of data ...effectively. Kernel principal ... See full document
11
Fast Tensor Principal Component Analysis via Proximal Alternating Direction Method with Vectorized Technique
... In the following part, we show how to solve these subproblems in the algo- rithm through a linearized way with vectorized technique. After all these sub- problems solved, we will give the framework of the algorithm that ... See full document
10
Power Quality Data Compression Based on Iterative PCA Algorithm in Smart Distribution Systems
... PQ analysis, a multichannel data com- pression based on iterative PCA (principal component analysis) algorithm is ...an iterative method is proposed to compute the ... See full document
13
Classification of EMG Signals for Assessment of Neuromuscular Disorders
... classification. Fast Fourier transform (FFT) and principal component analysis (PCA) was used on sEMG signals taken from bicep brachii muscle and the classifications of neuromuscular disorders ... See full document
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