A signal invariant wavelet function selection algorithm.
This paper addresses the problem of mother wavelet selection for wavelet signal processing in feature extraction and pattern recognition. The problem is formulated as an optimization criterion, where a wavelet library is defined using a set of parameters to find the best mother wavelet function. For...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 54; no. 4; pp. 629 - 643 |
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| Autor principal: | |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=113881208&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113881208 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2016 vid: 54 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 113881208 113881208 NLM26253283 113881208 10.1007/s11517-015-1354-z NLM26253283 113881208 ppf: 629 ppct: 14 formats: fmt: @attributes: type: P tig: atl: A signal invariant wavelet function selection algorithm. aug: au: Garg, Girisha affil: Babu Banarasi Das Institute of Technology, Ghaziabad India sug: subj: Algorithms Signal Processing, Computer Assisted Analysis of Variance Computer Simulation Human ab: This paper addresses the problem of mother wavelet selection for wavelet signal processing in feature extraction and pattern recognition. The problem is formulated as an optimization criterion, where a wavelet library is defined using a set of parameters to find the best mother wavelet function. For estimating the fitness function, adopted to evaluate the performance of the wavelet function, analysis of variance is used. Genetic algorithm is exploited to optimize the determination of the best mother wavelet function. For experimental evaluation, solutions for best mother wavelet selection are evaluated on various biomedical signal classification problems, where the solutions of the proposed algorithm are assessed and compared with manual hit-and-trial methods. The results show that the solutions of automated mother wavelet selection algorithm are consistent with the manual selection of wavelet functions. The algorithm is found to be invariant to the type of signals used for classification. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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