Discovery of Ill–Known Motifs in Time Series Data
«“The book under review provides one such vantage point, and anyone whose work involves finding patterns in large amounts of data should take heed. … For those well versed in the mathematics of harmonics and waves, the book should prove very useful in showing how these theories can be applied to data series. But even those who are not specialists in this area, such as myself, can still gain many ideas from this useful tome.” (Eugene Callahan, Computing Reviews, October 11, 2022)»
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. Les mer
Detaljer
- Forlag
- Springer Vieweg
- Innbinding
- Paperback
- Språk
- Engelsk
- Sider
- 205
- ISBN
- 9783662642146
- Utgivelsesår
- 2021
- Format
- 24 x 17 cm
Anmeldelser
«“The book under review provides one such vantage point, and anyone whose work involves finding patterns in large amounts of data should take heed. … For those well versed in the mathematics of harmonics and waves, the book should prove very useful in showing how these theories can be applied to data series. But even those who are not specialists in this area, such as myself, can still gain many ideas from this useful tome.” (Eugene Callahan, Computing Reviews, October 11, 2022)»