Convolutive Nonlinear Separation with Unsupervised Neural Network
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In this paper we propose a separating system for convolutive nonlinear mixtures, since it is rare to find linear instantaneous mixture in practical problems. The observed mixtures are first transformed into frequency domain and then separated on each frequency bin. After solved permutation problem, estimates are obtained. We show results of simulations with acoustic signals both of instantaneous and convolutive mixtures.
- IEEJ Transactions on Electronics, Information and Systems
IEEJ Transactions on Electronics, Information and Systems 126(8), 942-949, 2006-08-01
The Institute of Electrical Engineers of Japan