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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 the first part, many sparsity-based separation methods rely on the use of clustering techniques to identify the samples of the mixtures due to each sound...
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. Classical solutions use clock synchronization protocols and algorithms in the communication layer, but these alternatives do not tackle the lack of synchronization...
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