Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 1117 for “"Component analysis"”.
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Generalized Principal Component Analysis
… is to extend the classical Principal Components Analysis (PCA), aiming to reduce the dimensionality of a large number of Normal interrelated variables, in two directions. The first is to go beyond the static (contemporaneous or synchronous) covariance matrix among these interrelated …
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Independent component analysis and beyond
'Independent component analysis' (ICA) ist ein Werkzeug der statistischen Datenanalyse und Signalverarbeitung, welches multivariate Signale in ihre Quellkomponenten zerlegen kann. Obwohl das klassische ICA Modell sehr nützlich ist, gibt es viele Anwendungen, die Erweiterungen von ICA erfordern. In …
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Emotion and psychopathy: a three-component analysis
The study was designed to examine the hypothesis that psychopathy is associated with an affective deficit. Subjects were 42 incarcerated offenders divided into nonpsychopathic and psychopathic groups based on their scores on the Hare Revised Psychopathy Checklist (Hare, 1991). Facial expressions, …
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Study on Methods of Simultaneous Multi-Component Analysis.
… algorithms to assist in the quantitative analysis of multi-component samples in the hope of alleviating the need of tedious separation and cleanup procedures. These newer chemometric procedures tend to be complex and difficult to understand and implement and are successful under different …
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Appearance based object recognition using independent component analysis
… Karhunen-Loeve transform (KLT), or principal component analysis (PCA). The lower dimensional space has been called the eigenspace. For recognition, the test image is projected likewise onto the eigenspace and its position on the appearance manifold is used for the recognition phase. In object …
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Three-mode principal component analysis in designed experiments
… multivariate data, three-mode principal component analysis, to a three-way table with one observation per cell. It is based on the class of multiplicative models for three-way tables (s x t x u) whose general form has expectation E(y<sub>ijk</sub>) = μ + α<sub>i</sub> + β<sub>j</sub> + …
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Significance-linked connected component analysis+ for wavelet image coding
… REQUEST.] The Significance-Linked Connected Component Analysis+ (SLCCA+) is a efficient wavelet image coding algorithm that extends SLCCA by using new data organization and representation (DOR) and SLCCA+ use a definition of context model for the adaptive arithmetic coding. Extensive computer …
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Multivariate geostatistical simulation of compositional data using Principal Component Analysis
… modeling of compositional data using Principal Component Analysis (PCA). According to the methodology, grades are, first, transformed to log-ratios. Then, these log-ratios are linearly transformed to Principal Components (PCs). PCA tends to spatially decorrelate the factors, allowing for the …
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Enhancing brain-computer interfacing through advanced independent component analysis techniques
… etc. are used to reduce the noise and extract components of interest. However these methods process the data on the observed mixture domain which mixes components of interest and noise. Such a limitation means that extracted EEG signals possibly still contain the noise residue or coarsely that …
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Malarial Vaccination Studies: Bioassay Development, Antigen Fractionation, and Component Analysis
Made available in DSpace on 2015-05-14T14:57:11Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 7412190.PDF: 6189660 bytes, checksum: 06c14fc61492e3ab3730374206431976 (MD5) Previous issue date: 1973
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The value of independent component analysis in identifying climate processes
… a useful tool in the problem of identifying components of climate change signals from ensembles of multiple climate models.
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Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis
… between contrastive learning and neighborhood component analysis (NCA), we provide a novel stochastic nearest neighbor viewpoint of contrastive learning and subsequently propose a series of contrastive losses that outperform the existing ones. Under our proposed framework, we show a new …
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Quasi-objective Nonlinear Principal Component Analysis and applications to the atmosphere
NonLinear Principal Component Analysis (NLPCA) using three-hidden-layer feed-forward neural networks can produce solutions that over-fit the data and are non-unique. These problems have been dealt with by subjective methods during the network training. This study shows that these problems are …
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Radiation source detection from mobile sensor networks using principal component analysis
… and reconstruction method based on Principal Component Analysis (PCA) is proposed to work with mobile sensor networks. Two experiments are designed to test this method's performance on real-world data. The PCA-based method's performance is analyzed using receiver operating characteristic, or …
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Component Analysis of Conceptual Mediation in the Discrimination Learningof Young Children
Made available in DSpace on 2014-12-10T18:45:20Z (GMT). No. of bitstreams: 1 7212097.pdf: 2840369 bytes, checksum: d0e95befa1d1d1020506bddf2cf50a96 (MD5) Previous issue date: 1971
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Learning common sense knowledge from user interaction and principal component analysis
… network called ConceptNet. Using principal component analysis on the graph structure of ConceptNet yields AnalogySpace, a vector space representation of common sense knowledge. This representation reveals large-scale patterns in the data, while smoothing over noise, and predicts new …
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