This paper proposes Shared Component Analysis (SCA) as an alternative to Principal (PCA) for the purpose of dimensionality reduction neuroimaging data. The trend towards larger numbers recording sensors, pixels or voxels leads richer data, with finer spatial resolution, but it also inflates cost storage and computation risk overfitting. PCA can be used select a subset orthogonal components that...

Principal component analysis (PCA) is often used for analyzing data in the most diverse areas. In this work, we report an integrated approach to several theoretical and practical aspects of PCA. We start by providing, intuitive accessible manner, basic principles underlying PCA its applications. Next, present a systematic, though no exclusive, survey some representative works illustrating poten...

spatial patterns are useful descriptors of the horizontal structure in a plant population and may change over time as the individual components of the population grow or die out. but, whether this is the case for desert woody annuals is largely unknown. in the present investigation, the variations in spatial patterns of tribulus terrestris during different pulse events in semi-arid area of the ...

the writers of this research have studied seven variables including: precipitation, relative humidity, sunny hours, temperature average, temperature minimum, temperature maximum and sea level pressure, at sanandaj air station during 1964-1994. sanandaj air station has nearly 10966 days of complete data for these variables. a principal component analysis (pca) has been applied on this data; then...

background: metabolic syndrome (mets), a combination of coronary heart disease and diabetes mellitus risk factor, refer to one of the most challenging public health issues in worldwide. the aim of this study was to identify the subgroups of participants in a study on the basis of mets components.   methods: the cross-sectional study took place in the districts related to tehran university of me...

abstract soil quality evaluation is an essential issue in soil management for agriculture and natural resource protection. soil quality indices are useful tools for determination and comparison of soils quality. using of principle component analysis in this study we selected 6 important properties as a soil quality minimum data set (mds) among 18 soil properties (tds). then, soil quality of agr...

introduction: the accuracy of analyzing functional mri (fmri) data is usually decreases in the presence of noise and artifact sources. a common solution in for analyzing fmri data having high noise is to use suitable preprocessing methods with the aim of data denoising. some effects of preprocessing methods on the parametric methods such as general linear model (glm) have previously been evalua...