Articles liés à Online Component Analysis, Architectures and Applications
Synopsis
This monograph deals with principal component analysis (PCA), kernel component analysis (KPCA), and independent component analysis (ICA), highlighting their applications to streaming-data implementations. The basic concepts related to PCA, KPCA, and ICA are widely available in the literature; however, very few texts deal with their practical implementation in computationally limited resources. This monograph discusses the state-of-the-art online PCA and KPCA techniques in a unified and principled manner, presenting solutions that achieve a higher convergence speed and accuracy in many applications, particularly image processing. Besides, this work also explains how to remove various artifacts from data records based on blind source separation by independent component analysis implemented with ICA, splitting feature identification from feature separation. Herein, three FastICA online hardware architectures and implementation for biomedical signal processing are addressed. The main features are summarized as follows: 1) energy-efficient FastICA using the proposed early determination scheme; 2) cost-effective variable-channel FastICA using the Gram-Schmidt-based whitening algorithm; and 3) moving-window-based online FastICA algorithm with limited memory. The post-layout simulation results with artificial and EEG data validate the design concepts.
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- Éditeurnow publishers Inc
- Date d'édition2022
- ISBN 10 1638281165
- ISBN 13 9781638281160
- ReliureBroché
- Langueanglais
- Nombre de pages222
- Coordonnées du fabricantnon disponible
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This monograph deals with principal component analysis (PCA), kernel component analysis (KPCA), and independent component analysis (ICA), highlighting their applications to streaming-data implementations. The basic concepts related to PCA, KPCA, and ICA are widely available in the literature; however, very few texts deal with their practical implementation in computationally limited resources. This monograph discusses the state-of-the-art online PCA and KPCA techniques in a unified and principled manner, presenting solutions that achieve a higher convergence speed and accuracy in many applications, particularly image processing. Besides, this work also explains how to remove various artifacts from data records based on blind source separation by independent component analysis implemented with ICA, splitting feature identification from feature separation. Herein, three FastICA online hardware architectures and implementation for biomedical signal processing are addressed. The main features are summarized as follows: 1) energy-efficient FastICA using the proposed early determination scheme; 2) cost-effective variable-channel FastICA using the Gram-Schmidt-based whitening algorithm; and 3) moving-window-based online FastICA algorithm with limited memory. The post-layout simulation results with artificial and EEG data validate the design concepts. N° de réf. du vendeur 9781638281160
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