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Algebraic view on the PCA method in selected applications
 Hammerbauer, Tomáš ; Hnětynková, Iveta (advisor) ; Tichý, Petr (referee)
This thesis deals with describing algebraic and statistic view on Principal component analysis and the way of exporting important variables. Basic properties of the singular value decomposition are introduced and the best rank k aproximation of a matrix is de- rived. Then, a conection between PCA and singular value decomposition is described. At the end, PCA is ilustrated on two numerical experiments on image databases. It is shown, how we can aproximate images simillar to the elements of the database. Theo- retical foundations for the experiments are presented and then they are implemented in the Matlab enviroment. 1
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