Signal classification using smooth coefficients of multiple wavelets to achieve high accuracy from compressed representation of signal

Paul Grant, Md. Zahid Islam

Research output: Book chapter/Published conference paperConference paperpeer-review

Abstract

Classification of time series signals has become an important construct and has many practical applications. With existing classifiers, we may be able to classify signals accurately; however, that accuracy may decline if using a reduced number of attributes. Transforming the data and then undertaking a dimensionality reduction may improve the quality of the data analysis, decrease the time required for classification and simplify models. We propose an approach, which chooses suitable wavelets to transform the data, then combines the output from these transformations to construct a dataset by applying ensemble classifiers. We demonstrate this on different data sets across different classifiers and use different evaluation methods. Our experimental results demonstrate the effectiveness of the proposed technique, compared to the approaches that use either raw signal data or a single wavelet transform.
Original languageEnglish
Title of host publicationAdvanced Data Mining and Applications
Subtitle of host publicationADMA 2022
EditorsWeitong Chen, Lina Yao, Taotao Cai, Shirui Pan, Tao Shen, Xue Li
PublisherSpringer
Pages173-186
Number of pages14
Volume13726
ISBN (Electronic)9783031221378
ISBN (Print)9783031221361
DOIs
Publication statusPublished - 2022
Event18th International Conference on Advanced Data Mining and Applications 2022 - University of Wollongong, Brisbane, Australia
Duration: 28 Nov 202230 Nov 2022
https://adma2022.uqcloud.net/
https://adma2022.uqcloud.net/programme.html (Program)
https://link.springer.com/book/10.1007/978-3-031-22064-7 (Proceedings part 1)
https://link.springer.com/book/10.1007/978-3-031-22137-8 (Proceedings part 2)
https://adma2022.uqcloud.net/call_for_papers.html (Call for papers)
https://link-springer-com.ezproxy.csu.edu.au/content/pdf/bfm:978-3-031-22137-8/1 (Front matter)

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume13726
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Advanced Data Mining and Applications 2022
Country/TerritoryAustralia
CityBrisbane
Period28/11/2230/11/22
OtherThe 18th International Conference on Advanced Data Mining and Applications (ADMA'22) aims at bringing together the experts on data mining from around the world, and providing a leading international forum for the dissemination of original research findings in data mining, spanning applications, algorithms, software and systems, as well as different applied disciplines with potential in data mining. Papers will go through a full peer review process, and the accepted papers of the conference will be published by Springer in LNAI (Lecture Notes in Artificial Intelligence). The conference is rated B level in CORE ranking, and the accepted papers are indexed in EI and DBLP.
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