A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Reverberant signal separation using optimized complex sparse nonnegative tensor deconvolution on spectral covariance matrix
2018
Digital signal processing (Print)
In this paper, an optimized complex nonnegative tensor factor 2D deconvolution (CNTF2D) is proposed to separate the sources that have been mixed in an underdetermined reverberant environment. Unlike conventional methods, the proposed model decomposition is performed directly on the statistics in the form of spectral covariance matrix instead of the data itself (i.e. the mixed signal). For faster convergence the model is adapted under the hybrid framework of the generalized expectation
doi:10.1016/j.dsp.2018.07.018
fatcat:x5lvxsgfsnhbxobvd4rhyzye64