Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Cosme Llerena-Aguilar"'
Publikováno v:
Signal Processing. 134:166-173
Nowadays, some of the most successful sound source separation methods are based on the assumption of sparse sources. A large number of those separation solutions consist of two parts: the mixing matrix estimation and the separation stages. Concerning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72ceec12deed0d022bfc7acf925b9c35
https://doi.org/10.1016/j.sigpro.2016.12.001
https://doi.org/10.1016/j.sigpro.2016.12.001
Autor:
Cosme Llerena-Aguilar, Francisco Llerena, Manuel Utrilla-Manso, Roberto Gil-Pita, David Ayllón, Manuel Rosa-Zurera
Publikováno v:
Signal Processing. 118:177-187
Desynchronization degrades the performance of many signal processing algorithms in Wireless Acoustic Sensor Networks. It is mainly caused by the different distances between the source and each node and by the clock phase offset and frequency skew. Cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::496dbb473b3c6b207f6b2e5979e4b266
https://doi.org/10.1016/j.sigpro.2015.06.023
https://doi.org/10.1016/j.sigpro.2015.06.023
Autor:
Inma Mohino-Herranz, Manuel Utrilla-Manso, Roberto Gil-Pita, Héctor A. Sánchez-Hevia, Manuel Rosa-Zurera, Cosme Llerena-Aguilar
Publikováno v:
SAM
Current research in the field of Wireless Acoustic Sensor Networks (WASN) is gradually introducing the use of sound spatial techniques in the field of binaural hearing aids, in which sound environment information must be extracted in order to tune up
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f3098211b131bfe76b1bb34245a144a
https://doi.org/10.1109/sam.2016.7569708
https://doi.org/10.1109/sam.2016.7569708
Publikováno v:
IEEE transactions on bio-medical engineering. 62(10)
A computationally efficient system for sound environment classification in digital hearing aids is presented in this paper. The goal is to automatically classify three different listening environments: “speech,” “music,” and “noise.” The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24b4a39b3a5270449f64dd3a2fe68fd5
https://pubmed.ncbi.nlm.nih.gov/25935024
https://pubmed.ncbi.nlm.nih.gov/25935024
Autor:
Guillermo Ramos-Auñón, Inma Mohino-Herranz, Héctor A. Sánchez-Hevia, David Ayllón, Cosme Llerena-Aguilar
Publikováno v:
Modelling, Identification and Control / 827: Computational Intelligence.
In this paper, we propose a computationally-efficient EEGbased stress detection that uses only two non-invasive electrodes. The system is designed to classify between two situations: high stress level or low stress level. A linear classifier is train
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5816c4091aae97019e904f90f01e9349
https://doi.org/10.2316/p.2015.827-023
https://doi.org/10.2316/p.2015.827-023
Publikováno v:
2011 IEEE Statistical Signal Processing Workshop (SSP).
Blind Source Separation algorithms have been applied to speech mixtures during many years, taking into account the knowledge and properties of speech signals. A new approach for speech separation based on sparse representations of speech has recently
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08bd4ebaca2bbe51f08dcf217589ad3e
https://doi.org/10.1109/ssp.2011.5967822
https://doi.org/10.1109/ssp.2011.5967822