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Signal separation and classification
Industrial Research’s signal separation and classification research focuses on: the development of blind source separation algorithms to provide enhanced separation of mixed signals or mixtures of signal plus noise or interference; and methods for classification and separation of signals based on higher dimensional signal representation.
Blindly separated
Blind source separation
Blind source separation has advanced to provide powerful algorithms that allow separation of signals without prior knowledge of the nature of the signals, interferers, noise or the mixing process. This capability can be combined with prior knowledge of the signals, such as probability density function, time or frequency sparsity, to separate signals previously considered irretrievable corrupted…Read more >>
Mixed/Corrupted signals
Subspace methods
Industrial Research is developing methods for classification and separation of signals based on higher dimensional signal representation. Applications include enhanced resolution, separation, communication or location estimation in acoustic or wireless reverberant situations. Read more >>