In this paper we propose an extension of time-domain Blind Source Separation algorithms by applying the well known proportionate and improved proportionate adaptive algorithms. These algorithms, known in the context of adaptive filtering, are able to use the sparseness of acoustic impulse responses of mixing environments and give better performances than standard algorithms. Some preliminary experimental results show the effectiveness of the proposed approach in terms of convergence speed. © Springer International Publishing Switzerland 2014.
Proportionate algorithms for Blind Source Separation / Scarpiniti, Michele; Comminiello, Danilo; Scardapane, Simone; Parisi, Raffaele; Uncini, Aurelio. - 26(2014), pp. 99-106. ((Intervento presentato al convegno 23rd Workshop of the Italian Neural Networks Society, WIRN 2013 tenutosi a Vietri sul Mare, Salerno nel 23 May 2013 through 24 May 2013. - SMART INNOVATION, SYSTEMS AND TECHNOLOGIES. [10.1007/978-3-319-04129-2_10].
Proportionate algorithms for Blind Source Separation
SCARPINITI, MICHELE;COMMINIELLO, DANILO;SCARDAPANE, SIMONE;PARISI, Raffaele;UNCINI, Aurelio
2014
Abstract
In this paper we propose an extension of time-domain Blind Source Separation algorithms by applying the well known proportionate and improved proportionate adaptive algorithms. These algorithms, known in the context of adaptive filtering, are able to use the sparseness of acoustic impulse responses of mixing environments and give better performances than standard algorithms. Some preliminary experimental results show the effectiveness of the proposed approach in terms of convergence speed. © Springer International Publishing Switzerland 2014.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
