Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

Language: English

Published by Birkhäuser, 2020

3030493946 / 9783030493943

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means.Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader's area of interest, or read together to provide a comprehensive overview of the topic.Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autonomous vehicles, wireless technology, and historical conservation.

Seller Inventory # 9783030493943

Title
Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint
Author
Mark K. Hinders
Publisher
Birkhäuser
Publication year
2020
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3030493946
ISBN 13
9783030493943
Item weight
705 grams
Dimensions
241x160x25 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item5 to 7 business days7 to 10 business days
First itemUS$ 35.42US$ 35.42
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