báo cáo hóa học:" Efficient methods for joint estimation of multiple fundamental frequencies in music signals"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Efficient methods for joint estimation of multiple fundamental frequencies in music signals | EURASIP Journal on Advances in Signal Processing SpringerOpen0 This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text HTML versions will be made available soon. Efficient methods for joint estimation of multiple fundamental frequencies in music signals EURASIP Journal on Advances in Signal Processing 2012 2012 27 doi 1687-6180-2012-27 Antonio Pertusa pertusa@ Jose M. Inesta inesta@ ISSN 1687-6180 Article type Research Submission date 11 April 2011 Acceptance date 14 February 2012 Publication date 14 February 2012 Article URL http content 2012 1 27 This peer-reviewed article was published immediately upon acceptance. It can be downloaded printed and distributed freely for any purposes see copyright notice below . For information about publishing your research in EURASIP Journal on Advances in Signal Processing go to http authors instructions For information about other SpringerOpen publications go to http 2012 Pertusa and Inesta licensee Springer. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Efficient methods for joint estimation of multiple fundamental frequencies in music signals Antonio Pertusa and José M Inesta Departamento de Lenguajes y Sistemas Informaticos Universidad de Alicante . Box 99 E-03080 Alicante Spain Corresponding author pertusa@ Email address JMI inesta@ Abstract This study presents efficient techniques for multiple fundamental frequency estimation in music signals. The proposed methodology can infer harmonic patterns from a mixture considering interactions with other sources and evaluate them in a joint estimation scheme. For this purpose a set of .

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