Abstract
In this paper we employ information theoretic algorithms, previously used for separating instantaneous mixtures of sources, for separating convolved mixing in the frequency domain. It is observed that convolved mixing in the time domain corresponds to instantaneous mixing in the frequency domain. Such mixing can be inverted using simpler and more robust algorithms than the ones recently developed. Advantages of this approach are improved efficiency and better convergence features.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 21-34 |
| Number of pages | 14 |
| Journal | Neurocomputing |
| Volume | 22 |
| Issue number | 1-3 |
| DOIs | |
| State | Published - Nov 20 1998 |
| Externally published | Yes |
Keywords
- Convolved mixtures
- Frequency domain
- Information theoretic algorithms
- Separation
ASJC Scopus subject areas
- Computer Science Applications
- Cognitive Neuroscience
- Artificial Intelligence