Téléchargez le livre : Discovery of Ill–Known Motifs in Time Series Data

Discovery of Ill–Known Motifs in Time Series Data



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Éditeur :

Springer Vieweg


Collection :

Technologien für die intelligente Automation

Paru le : 2021-10-01



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Description

This book includes a novel motif discovery for time series, KITE (ill-Known motIf discovery in Time sEries data), to identify ill-known motifs transformed by affine mappings such as translation, uniform scaling, reflection, stretch, and squeeze mappings. Additionally, such motifs may be covered with noise or have variable lengths. Besides KITE’s contribution to motif discovery, new avenues for the signal and image processing domains are explored and created.  The core of KITE is an invariant representation method called Analytic Complex Quad Tree Wavelet Packet transform (ACQTWP). This wavelet transform applies to motif discovery as well as to several signal and image processing tasks. The efficiency of KITE is demonstrated with data sets from various domains and compared with state-of-the-art algorithms, where KITE yields the best outcomes.
Pages
205 pages
Collection
Technologien für die intelligente Automation
Parution
2021-10-01
Marque
Springer Vieweg
EAN papier
9783662642146
EAN PDF
9783662642153
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
20
Taille du fichier
5765 Ko
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Prix
89,66 €

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