Technologien für die intelligente Automation

Deppe, Sahar

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.

Details

Published by: Springer Vieweg

Publication Date: 2021-10-02

Format: Paperback

ISBN-13: 9783662642146

DOI: 10.1007/978-3-662-64215-3

Dimensions: 240cm x168cm

Pages: 205