Abstract / Description of output
This paper examines the performance of a blind signal separation system that uses information maximisation techniques, when applied to signals with non-stationary characteristics. It assesses the effectiveness of different methods of removing or reducing the degree of non-stationarity of the source signals, in terms of the level of separation achieved after a fixed training period
Original language | Undefined/Unknown |
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Title of host publication | Proceedings of the 1998 IEEE Signal Processing Society Workshop Neural Networks for Signal Processing VIII |
Pages | 113-122 |
Number of pages | 10 |
DOIs | |
Publication status | Published - 1 Aug 1998 |
Keywords / Materials (for Non-textual outputs)
- adaptive signal detection, information theory, learning (artificial intelligence), neural nets, optimisationblind signal separation, information theory, information-maximisation, learning, neural nets, signal nonstationarity