ZCR-aided neurocomputing: A study with applications

• Autor(a) principal: Guido, Rodrigo Capobianco [UNESP]
• Data de Publicação: 2016
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.knosys.2016.05.011; http://hdl.handle.net/11449/178039
• topic: Biomedical signal analysis; Feature extraction (FE); Image border extraction; Pattern recognition and knowledge-based systems (PRKbS); Speech segmentation; Zero-crossing rates (ZCRs)

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.