Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint (Record no. 76765)

000 -LEADER
fixed length control field 03929nam a22006135i 4500
001 - CONTROL NUMBER
control field 978-3-030-49395-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801214811.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200701s2020 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783030493950
-- 978-3-030-49395-0
082 04 - CLASSIFICATION NUMBER
Call Number 621.382
100 1# - AUTHOR NAME
Author Hinders, Mark K.
245 10 - TITLE STATEMENT
Title Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2020.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIV, 346 p. 208 illus., 143 illus. in color.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Background and history -- Intelligent structural health monitoring with ultrasonic lamb waves -- Automatic detection of flaws in recorded music -- Pocket depth determination with an ultrasonographic periodontal probe -- Spectral intermezzo: Spirit security systems -- Lamb wave tomographic rays in pipes -- Classification of RFID tags with wavelet fingerprinting -- Pattern classification for interpreting sensor data from a walking-speed robot -- Cranks and charlatans and deepfakes.
520 ## - SUMMARY, ETC.
Summary, etc 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-030-49395-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2020.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Biomedical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Materials—Analysis.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Robotics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Automation.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing .
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Biomedical Engineering and Bioengineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Materials Characterization Technique.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control, Robotics, Automation.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
912 ## -
-- ZDB-2-ENG
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-- ZDB-2-SXE

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