Artículos relacionados a Comprehensive Guide to Dynamic Time Warping in Python

Comprehensive Guide to Dynamic Time Warping in Python - Tapa blanda

Gulzar, Hafiz Muhammad

 
9786139858026: Comprehensive Guide to Dynamic Time Warping in Python
Tapa blanda
ISBN 10: 613985802X ISBN 13: 9786139858026
Editorial: LAP LAMBERT Academic Publishing, 2018

Sinopsis

Dynamic Time Warping (DTW) is a well-known technique used to determine alignment between two temporal sequences. DTW has been used in wide range of applications and it can be applied on any data which can be represented as linear sequence. Existing DTW libraries have out dated implementation of core DTW algorithm, which result in low performance or are inapplicable for big sequences. The aim of this book is to present, detailed concept of DTW along with a comprehensive DTW library, encapsulating the implementation of DTW variants with recently proposed efficient algorithms. Further down the road, in this book I presented a python module for computing and visualizing DTW alignment: DTWPy. DTWPy has implementation of classical DTW and recently proposed performance efficient algorithms i.e. fastDTW and DDTW. Correctness of the algorithms is verified by comparing it with existing R implementation. This book gives the basic idea to the readers about what DTW is and DTWPy have the most comprehensive implementation of DTW algorithms present in literature to date, and is applicable on large temporal sequence.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

Dynamic Time Warping (DTW) is a well-known technique used to determine alignment between two temporal sequences. DTW has been used in wide range of applications and it can be applied on any data which can be represented as linear sequence. Existing DTW libraries have out dated implementation of core DTW algorithm, which result in low performance or are inapplicable for big sequences. The aim of this book is to present, detailed concept of DTW along with a comprehensive DTW library, encapsulating the implementation of DTW variants with recently proposed efficient algorithms. Further down the road, in this book I presented a python module for computing and visualizing DTW alignment: DTWPy. DTWPy has implementation of classical DTW and recently proposed performance efficient algorithms i.e. fastDTW and DDTW. Correctness of the algorithms is verified by comparing it with existing R implementation. This book gives the basic idea to the readers about what DTW is and DTWPy have the most comprehensive implementation of DTW algorithms present in literature to date, and is applicable on large temporal sequence.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2018
Idioma
Inglés
ISBN 10 
613985802X
ISBN 13 
9786139858026
Encuadernación
Tapa blanda
Número de páginas
60
Contacto del fabricante
no disponible
Persona responsable
no disponible