Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

Authors: Hinders, Mark K.

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  • Presents the dynamic wavelet fingerprint technique of identifying machine learning features
  • Discusses numerous real-world applications, including in the medical, vehicle and wireless technology
  • Structures chapters in a self-contained way, allowing for chapters to be read individually
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eBook $139.00
price for USA in USD
  • ISBN 978-3-030-49395-0
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  • Immediate eBook download after purchase
Hardcover $179.99
price for USA in USD
  • ISBN 978-3-030-49394-3
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  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
About this book

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.


About the authors

Professor Mark K. Hinders holds BS, MS and PhD degrees in Aerospace and Mechanical Engineering from Boston University, and is currently a Professor of Applied Science at the College of William & Mary in Virginia. Before coming to Williamsburg in 1993, Professor Hinders served as a Senior Scientist at Massachusetts Technological Laboratory, Inc., and as a Research Assistant Professor at Boston University. Before that he was an Electromagnetics Research Engineer at USAF Rome Laboratory located at Hanscom AFB, MA. Professor Hinders is currently conducting research in wave propagation and scattering phenomena as applied to medical imaging, intelligent robotics, security screening, remote sensing and nondestructive evaluation. He and his students are studying the interactions of acoustic, ultrasonic, elastic, thermal, electromagnetic and optical waves with various materials, tissues and structures. He is a founding member of the Applied Science Department and former Graduate Director and Department Chair.

Table of contents (9 chapters)

Table of contents (9 chapters)

Buy this book

eBook $139.00
price for USA in USD
  • ISBN 978-3-030-49395-0
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA in USD
  • ISBN 978-3-030-49394-3
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint
Authors
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
eBook ISBN
978-3-030-49395-0
DOI
10.1007/978-3-030-49395-0
Hardcover ISBN
978-3-030-49394-3
Edition Number
1
Number of Pages
XIV, 346
Number of Illustrations
65 b/w illustrations, 143 illustrations in colour
Topics