4.7 Article

ZCR-aided neurocomputing: A study with applications

期刊

KNOWLEDGE-BASED SYSTEMS
卷 105, 期 -, 页码 248-269

出版社

ELSEVIER
DOI: 10.1016/j.knosys.2016.05.011

关键词

Zero-crossing rates (ZCRs); Pattern recognition and knowledge-based systems (PRKbS); Feature extraction (FE); Speech-segmentation; Image border extraction; Biomedical signal analysis

资金

  1. CNPQ - Conselho Nacional de Pesquisa e Desenvolvimento in Brazil [306811/2014-6]

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This paper covers a particular area of interest in pattern recognition and knowledge-based systems (PRKbS), being intended for both young researchers and academic professionals who are looking for a polished and refined material. Its aim, playing the role of a tutorial that introduces three feature extraction (FE) approaches based on zero-crossing rates (ZCRs), is to offer cutting-edge algorithms in which clarity and creativity are predominant. The theory, smoothly shown and accompanied by numerical examples, innovatively characterises ZCRs as being neurocomputing agents. Source-codes in C/C++ programming language and interesting applications on speech segmentation, image border extraction and biomedical signal analysis complement the text. (C) 2016 Elsevier B.V. All rights reserved.

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