Method of the Principal Component
A Clutter Suppression Method Based on Improved Principal Component Selection Rule for Ground Penetrating Radar
... improved principal component selection rule based on difference spectrum of singular value and FCM is proposed in the ...the principal component range of direct wave and strong target signal, ...
11
Fast Tensor Principal Component Analysis via Proximal Alternating Direction Method with Vectorized Technique
... tensor principal component analysis is proposed which is called Linearized Alternating Direction Method with Vectorized technique for Tensor Principal Component Analysis ...
10
Defect Detection in Alphonso using Statistical Method and Principal Component Analysis: A Non-Destructive Approach
... Thus, we have proposed to investigate the defects in the alphonso mangoes by using statistical method to locate the defect effectively along with the Principal Component Analysis [5, 6] to lower the ...
5
Optimization of Process Parameter in Turning of Copper by Combination of Taguchi and Principal Component Analysis Method
... PCA method coupled with grey based Taguchi method is implemented as multi response optimization problem cannot solved by other optimization methods In this method orthogonal array and signal to noise ...
6
The Attribute Optimization Method Based on the Probability Kernel Principal Component Analysis and Its Application
... The principal component analysis (PCA) is the most common attribute optimization analysis techniques, but it is a linear method and exists the problem of lack of probability model and the absence of ...
6
Generalized Power Method for Sparse Principal Component Analysis
... sparse principal component analysis (sparse ...dominant principal component of a data matrix, or more com- ponents at once, ...gradient method suited for the ...
37
Face Recognition Using Principal Component Analysis Method
... research, Principal component analysis approach to the face recognition problem was studied and a face recognition system based on the eigenfaces approach was ...this method gave very good ...
5
Nonlinear principal component analysis: An alternative method for finding patterns in environmental data.
... By treating the descriptors (environmental variables) as a variety of measurement types, the use of non-linear principal components analysis (PCA) provided a gain in explained variation of 10 per cent for the 1st ...
11
Fault Detection of The Tennessee Eastman Process Using Improved PCA and Neural Classifier
... The idea of key dimension selection in classification is select a subset of dimension in which classification result is better or comparable than the result obtained from the full set of dimensions. This paper is used ...
6
A 2-Dimensional Gabor-Filters for Face Recognition System: A Survey
... like principal component analysis (PCA), independent component analysis (ICA) and Fisher’s linear discriminant analysis (LDA) have been extensively identified to be successful and commonly used ...
9
A Wireless Signal Denoising Model for Human Activity Recognition
... The contributions of our works are as follows. Firstly, we utilize traditional average filter algorithms to reduce noise of wireless signals and analyze their differences, which is effective to remove the environment ...
11
Component retention in principal component analysis with application to cDNA microarray data
... 3.3 Summary of results For six microarray data sets Table 2 summarizes the results of the stopping criteria for six microarray data sets. Note that Bartlett's test fails to dis- card any components. The null hypothesis ...
21
A SURVEY: PRINCIPAL COMPONENT ANALYSIS (PCA)
... simplest method for determining which face class provides the best description of an input facial image is to find the face class k that minimizes the Euclidean distance ...
9
Dimensionality Reduction of Image Feature Based on Mean Principal Component Analysis
... include Principal Component Analysis (PCA) and linear Discriminant Analysis ...reduction method, the more representative is the kernel based method and the method based on manifold ...
8
Study on comprehensive quantitative classification and evaluation method of development index
... analysis method, these variables are often not independent, there is a complex relationship, and bring certain difficulty to the comprehensive ...variables, principal component, so as a small number ...
7
Multivariate Analysis in Upland Cotton (Gossypium hirsutum L.)
... of principal component analysis combined with clustering of Ward’s minimum variance method in genetic divergence studies in cotton was supported by Rajamani and Mallikarjuna Rao (2009), Vijaya ...
8
Association tests based on the principal component analysis
... In this paper, we proposed using PC scores for the associ- ation test as an alternative to the haplotype-based test. The use of PC scores has the effect of reducing the number of parameters in logistic regression. The ...
5
II. THE CLASSICAL PRINCIPAL COMPONENT ANALYSIS (PCA)
... efficient method, but MVV still takes a few more times in the computation when the dimension p is larger than 100; that is around ...new method for robust principal component ...PCA ...
5
Principal component gene set enrichment (PCGSE)
... approach, principal component gene set enrichment (PCGSE), for unsupervised gene set testing relative to the sample PCs of genomic ...PCGSE method computes the statistical association between gene ...
18
Blind interference suppression for satellite navigation signals based on antenna arrays
... the principal component analysis into the power minimization method, a novel method for strong interference sup- pression has been proposed for satellite navigation applications, where the ...
5