The rapid increase in generating and collecting data with high resolution and recording frequency due to the availability and affordability of measurement technology is resulting in huge data archives that are growing exponentially in size. This explosive growth in accumulated data has generated an urgent need for new techniques and tools that can automatically support engineers and data analysts in transforming the enormous amounts of data into useful information and knowledge. In this book, we introduce a novel method for analyzing multidimensional data sets and discovering index vectors by the use of discontinuity detection. Jumps in data are detected using wavelet coefficients that are calculated dynamically for every level of wavelet coefficients. The discovered index vectors of the analyzed channels (raw data) are related in a dynamic alignment of tree-like structure. Channels are in relation according to a number of variables that are set adaptively such as the allowable average alignment difference between two discontinuity events. This method is implemented and tested against real automotive emission test data.
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Hussam A. Hseiki, ME: Computer and Communication Engineering at the American University of Beirut, BE: Computer and Electrical Engineering. Project Manager in the Lebanese Army
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : moluna, Greven, Allemagne
Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hseiki HussamHussam A. Hseiki, ME: Computer and Communication Engineering at nthe American University of Beirut, BE: Computer and Electrical nEngineering. Project Manager in the Lebanese ArmyThe rapid increase in generating and c. N° de réf. du vendeur 4961598
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid increase in generating and collecting data with high resolution and recording frequency due to the availability and affordability of measurement technology is resulting in huge data archives that are growing exponentially in size. This explosive growth in accumulated data has generated an urgent need for new techniques and tools that can automatically support engineers and data analysts in transforming the enormous amounts of data into useful information and knowledge. In this book, we introduce a novel method for analyzing multidimensional data sets and discovering index vectors by the use of discontinuity detection. Jumps in data are detected using wavelet coefficients that are calculated dynamically for every level of wavelet coefficients. The discovered index vectors of the analyzed channels (raw data) are related in a dynamic alignment of tree-like structure. Channels are in relation according to a number of variables that are set adaptively such as the allowable average alignment difference between two discontinuity events. This method is implemented and tested against real automotive emission test data. N° de réf. du vendeur 9783639146158
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. An Adaptive Hierarchical Data Structure Searching Data Archives | Wavelets, Data structures, Information storage and retrieval systems, and Data mining | Hussam Hseiki | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639146158 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101543222
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock. N° de réf. du vendeur 3639146158
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