Header logo is ei

Separating convolutive mixtures by pairwise mutual information minimization", IEEE Signal Processing Letters

2007

Article

ei


Blind separation of convolutive mixtures by minimizing the mutual information between output sequences can avoid the side effect of temporally whitening the outputs, but it involves the score function difference, whose estimation may be problematic when the data dimension is greater than two. This greatly limits the application of this method. Fortunately, for separating convolutive mixtures, pairwise independence of outputs leads to their mutual independence. As an implementation of this idea, we propose a way to separate convolutive mixtures by enforcing pairwise independence. This approach can be applied to separate convolutive mixtures of a moderate number of sources.

Author(s): Zhang, K. and Chan, L.
Journal: IEEE Signal Processing Letters
Volume: 14
Number (issue): 12
Pages: 992-995
Year: 2007
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0

Links: Web

BibTex

@article{ZhangC2007,
  title = {Separating convolutive mixtures by pairwise mutual information minimization", IEEE Signal Processing Letters},
  author = {Zhang, K. and Chan, L.},
  journal = {IEEE Signal Processing Letters},
  volume = {14},
  number = {12},
  pages = {992-995},
  year = {2007}
}