|
|
|
|
|
Waqas Rafique, Jonathon Chambers and Ali Imam Sunny
The performance of the independent vector analysis (IVA) algorithm depends on the choice of the source prior to better model the speech signals as it employs a multivariate source prior to retain the dependency between frequency bins of each source. Iden...
ver más
|
|
|
|
|
|
|
|
|
Kanghyu Lee, Junmuk Lee, Changwoo Ha, Minseok Han and Hanseok Ko
Driver assistance systems are a major focus of the automotive industry. Although technological functions that help drivers are improving, the monitoring of driver state functions receives less attention. In this respect, the human heart rate (HR) is one ...
ver más
|
|
|
|
|
|
|
|
|
Maoshen Jia, Jundai Sun and Xiguang Zheng
In this work, a multiple speech source separation method using inter-channel correlation and relaxed sparsity is proposed. A B-format microphone with four spatially located channels is adopted due to the size of the microphone array to preserve the spati...
ver más
|
|
|
|
|
|
|
|
|
Cancan Yi, Yong Lv, Han Xiao, Guanghui You and Zhang Dang
To improve the performance of single-channel, multi-fault blind source separation (BSS), a novel method based on regenerated phase-shifted sinusoid-assisted empirical mode decomposition (RPSEMD) is proposed in this paper. The RPSEMD method is used to dec...
ver más
|
|
|
|
|
|
|
|
|
Dan Yang, Cancan Yi, Zengbin Xu, Yi Zhang, Mao Ge and Changming Liu
To solve the problem of multi-fault blind source separation (BSS) in the case that the observed signals are under-determined, a novel approach for single channel blind source separation (SCBSS) based on the improved tensor-based singular spectrum analysi...
ver más
|
|
|
|