Global ETD Search
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Showing 1 to 4 of 4 for “"kernel PCA"”.
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Integrating Principal Component Analysis and Deep Learning Methods for Data Representation and Image Denoising
… with a focus on Principal Component Analysis (PCA) and its nonlinear counterparts. The main aim is to review the PCA machinery and assess its effectiveness on real data and images. Two prototype tasks and a comparative denoising study are considered. First, PCA is derived via standardization, …
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Modeling and Recognizing Binary Human Interactions
… those challenges by carefully designing a kernel-based approach that combines non-linear dynamical system modeling with kernel PCA. Experimental results computed on three recently published datasets, clearly show the promise of this approach, where the classification accuracy, and the …
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Time domain classification of transient RFI
… is analysed for principal components analysis (PCA) and kernel PCA, the latter proving most suitable. The effect of the supply voltage of certain RFI sources on cluster separation in the principal components domain is also explored. Several na¨ıve classification algorithms are tested, using …
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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 …