%0 Conference Proceedings
%T Conceptualization and Significance Study of a New Appliation CS-MIR
%+ Department of Informatics [King's College London]
%+ Digital Ecosystems and Business Intelligence Institute [Curtin University of Technology]
%+ Department of Mathematics and Computer Science
%A Chang, Kaichun, K.
%A Barton, Carl
%A Iliopoulos, Costas, S.
%A Jang, Jyh-Shing, Roger
%Z Part 4: Learning and Data Mining
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI)
%C Halkidiki, Greece
%Y Lazaros Iliadis
%Y Ilias Maglogiannis
%Y Harris Papadopoulos
%I Springer
%3 Artificial Intelligence Applications and Innovations
%V AICT-381
%N Part I
%P 146-156
%8 2012-09-27
%D 2012
%R 10.1007/978-3-642-33409-2_16
%K compressive sampling
%K music information retrieval
%K music identification
%Z Computer Science [cs]Conference papers
%X Numerous researches on Music Information Retrieval (MIR) have been estimated and linked with sparse representation method, few has paid enough attention on the application of compressive sensing and how it affects the reconstruction of MIR. This paper provides solid theoretical and various empirical evidence on the conceptualization, theoretical development, and implication of Compressive Sensing (CS), which to great extent, contributes to the application of the Music Information Retrieval.
%G English
%2 https://inria.hal.science/hal-01521427/document
%2 https://inria.hal.science/hal-01521427/file/978-3-642-33409-2_16_Chapter.pdf
%L hal-01521427
%U https://inria.hal.science/hal-01521427
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-AIAI
%~ IFIP-WG12-5
%~ IFIP-AICT-381