Retrieving the correlation matrix from a truncated PCA solution: The inverse principal component problem

Psychometrika ◽  
1999 ◽  
Vol 64 (3) ◽  
pp. 317-324 ◽  
Author(s):  
Jos M. F. ten Berge ◽  
Henk A. L. Kiers
Keyword(s):  
Correlation Matrix ◽  
Principal Component ◽  
Component Problem

scholarly journals Non-Orthogonal Multiple Access in Multiuser MIMO Configurations via Code Reuse and Principal Component Analysis

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1330
Author(s):  
Panagiotis K. Gkonis ◽  
Panagiotis T. Trakadas ◽  
Lambros E. Sarakis
Keyword(s):  
Principal Component Analysis ◽  
Interference Cancellation ◽  
Correlation Matrix ◽  
Multiple Access ◽  
Multiple Input Multiple Output ◽  
Principal Component ◽  
Component Analysis ◽  
Inner Product ◽  
Transmission Scheme ◽  
Code Reuse

The goal of the study presented in this paper is to evaluate the performance of a proposed transmission scheme in multiuser multiple-input multiple-output (MIMO) configurations, via code reuse. Hence, non-orthogonal multiple access (NOMA) is performed. To this end, a correlation matrix of the received data is constructed at the transmitter, with feedback as only the primary eigenvector of the equivalent channel matrix, which is derived after principal component analysis (PCA) at the receiver. Afterwards, users experiencing improved channel quality (i.e., diagonal terms of the correlation matrix) along with reduced multiple access interference (i.e., the inner product of transmission vectors) are the potential candidates for their assigned code to be reused. As the results indicate, considering various MIMO configurations, the proposed approach can achieve almost 33% code assignment gain (CAG), when successive interference cancellation (SIC) is employed in mobile receivers. However, even in the absence of SIC, CAG is still maintained with a tolerable average bit error rate (BER) degradation.

An Evaluation Method Based on Grey Incidence Coefficient and Double-Point Method

2011 ◽  
Vol 50-51 ◽  
pp. 766-769
Author(s):  
Pu Yu Hao ◽  
Bao Feng Li ◽  
Yu Huan Cui
Keyword(s):  
Principal Component Analysis ◽  
Correlation Matrix ◽  
Double Point ◽  
Evaluation Method ◽  
Correlation Method ◽  
Principal Component ◽  
Point Method ◽  
Economic Indicators ◽  
Evaluation Indexes ◽  
Main Factors

To one company, it takes 8 major economic indicators as evaluation indexes. Firstly, it uses correlation method to determine the weight and uses the double-point method to sort the 8-years comprehensive economic enterprises. Then through the analysis of the correlation matrix, it identifies the main factors. Finally, the ranking and principal component analysis results are compared and analyzed.

Investigation of Soil Heavy Metal in Zhehai Town Huize County Yunnan Based on GIS- Approach and Geostatistics

2012 ◽  
Vol 610-613 ◽  
pp. 3067-3074
Author(s):  
Kun Shi ◽  
Dong Sheng Li ◽  
Bi Yun Zhao
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Correlation Matrix ◽  
Yunnan Province ◽  
Anthropogenic Activities ◽  
Principal Component ◽  
And Cluster Analysis ◽  
Soil Area

1144 sample points were collected using PXRF from an area of 99 square kilometers soil area Zhehai town Huizhe county of Yunnan province to acquire their concentrations and possible sources, and characterize their spatial variability for risk assessment. SPSS16.0 was used to deal the raw date and eliminate the outfits and perform Multivariate analysis (correlation matrix, principal component analysis, and cluster analysis). It discriminate distinct groups of heavy metals. From the Range of the semi-variorum models, it obtained elements spatial structure and the contamination resource caused mainly by natural resource or anthropogenic activities. The result of risk assessment attained the percentage of pollution accounts for whole investigate region, which provides the reference to deal with the soil pollution.

Morphological variation in the Pacific sand dollar Dendraster excentricus

1995 ◽  
Vol 73 (3) ◽  
pp. 576-583
Author(s):  
Raymond K. Nakamura
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Morphological Variation ◽  
Correlation Matrix ◽  
Principal Component ◽  
Sand Dollar ◽  
Coastal Habitats ◽  
Point Conception ◽  
The Pacific ◽  
Dendraster Excentricus

Correlations between latitude, habitat, and morphology in the Pacific sand dollar Dendraster excentricus were identified with principal component analysis. Twenty-two lengths were measured on the oral and aboral surfaces of 615 specimens from 31 sites. Samples were divided at latitude 34°30′N (Point Conception) and into bay and coastal habitats by relative wave exposure. Principal components (PC) were estimated from a correlation matrix of sample means of log-transformed measurements. PC1 accounted for 90% of the variance and was a measure of overall size. All 22 PC1 coefficients were positive and differed significantly from 0, according to a jackknifing test. PC1 differed significantly with latitude (ANOVA, p < 0.01) but not habitat. Southern populations tended to be smaller. PC2 accounted for 5% of the variance and described overall shape. Of the 22 variables, 13 had significant coefficients that varied in sign. PC2 varied significantly with habitat (ANOVA, p < 0.05) but not latitude. In coastal populations, the peristome and petaloids tended to be more posteriorly positioned and the food grooves were branched more peripherally. These features correspond to the greater tendency for coastal specimens to use their posterior end to suspension feed.

scholarly journals Effect of rainfall variability on the production of Vigna unguiculata (L.) Walp. in the semi-arid region of Paraíba

2020 ◽  
Vol 13 (9) ◽  
pp. 26
Author(s):  
L. D. R. Silva ◽  
P. H. A. Cartaxo ◽  
M. C. Silva ◽  
K. S. Gonzaga ◽  
D. B. Araújo ◽  
...  
Keyword(s):  
Vigna Unguiculata ◽  
Agricultural Production ◽  
Correlation Matrix ◽  
Rainfall Variability ◽  
Principal Component ◽  
Strong Reduction ◽  
Semi Arid Region ◽  
The Relationship ◽  
Production Dynamics ◽  
Semi Arid

Agricultural production in semi-arid areas of the globe is dependent on species adapted to conditions of low availability of resources, such as water. Cowpea (Vigna unguiculata L. Walp.) is a vegetable widely grown in regions with water restrictions, however, even with its good adaptability, it is vulnerable to the effects of prolonged droughts. In this sense, this research aimed to analyze the influence of rainfall patterns on the production dynamics of cowpea during the period of fifteen years (2002-2016) in the municipality of Conceição, Paraíba, Brazil. A correlation matrix was used to analyze the influence of precipitation on the production variables of the cowpea crop, as well as the relationship between these variables. Subsequently, the Principal Component Analysis (PCA) was carried out. The results showed a strong reduction in the production variables of cowpea from the year 2012, which is due to the reduction of rainfall in this period and was proven through the correction matrix, which showed a positive correlation of rainfall mainly with the planted and harvested area. The PCA recorded 91.02% of explanation in the first two axes, and demonstrated that for production and productivity, other factors in addition to good rainfall levels are necessary to increase the productive results of cowpea in the municipality.

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