dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T17:26:55Z
dc.date.available2018-12-11T17:26:55Z
dc.date.created2018-12-11T17:26:55Z
dc.date.issued2016-02-29
dc.identifierNeurocomputing, v. 179, p. 264-282.
dc.identifier1872-8286
dc.identifier0925-2312
dc.identifierhttp://hdl.handle.net/11449/177746
dc.identifier10.1016/j.neucom.2015.12.012
dc.identifier2-s2.0-84955697730
dc.identifier6542086226808067
dc.identifier0000-0002-0924-8024
dc.description.abstractThis tutorial, dedicated both to young professionals and students working with digital signal processing and pattern recognition, introduces three feature extraction approaches based on signal energy, characterising alternative and innovative ways for its use. The proposed theory, smoothly presented, is complemented with numerical examples, source-codes in C/C++ programming language, and applications in a diversity of computational problems, namely, neurophysiological signal processing, speech processing, and image processing. The lack of novelty in current energy-based approaches and the feasibility of a balance among creativity, simplicity, and accuracy constitutes the motivation for this text, which reveals how relevant the concept of signal energy may be, if properly employed.
dc.languageeng
dc.relationNeurocomputing
dc.relation1,073
dc.rightsAcesso restrito
dc.sourceScopus
dc.subjectFeature extraction
dc.subjectImage processing
dc.subjectNeurophysiological signal processing
dc.subjectPattern recognition
dc.subjectSignal energy
dc.subjectSpeech processing
dc.titleA tutorial on signal energy and its applications
dc.typeArtículos de revistas


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