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Symmetric adaptive maximum likelihood estimation for noise cancellation and signal separation

Symmetric adaptive maximum likelihood estimation for noise cancellation and signal separation

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The symmetric adaptive maximum likelihood estimation (SAMLE) algorithm is proposed. It is shown to be a generalisation of the symmetric adaptive decorrelation (SAD) algorithm for noise cancellation and signal separation. Both the SAD and SAMLE algorithms are applied to the separation of a mixture of natural speech recorded in a realistic acoustic environment. A comparative simulation confirms that the SAMLE algorithm provides superior separation capabilities.

Inspec keywords: maximum likelihood estimation; interference suppression; adaptive estimation; adaptive signal processing; adaptive filters

Other keywords: signal separation; SAMLE algorithm; noise cancellation; maximum likelihood estimation; symmetric adaptive MLE

Subjects: Other topics in statistics; Information theory; Signal processing and detection; Other topics in statistics

References

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      • S. Van Gervan , D. Van Compernolle , H.L. Nguyen Thi , C. Jutten . Blind separation ofsources: a comparative study of 2-nd and a 4-th order solution. Signal Process. VII:Theories and Appl. , 1153 - 1156
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      • Van Gerven, S.: `Adaptive noise cancellation and signal separation with applicationsto speech enhancement', 1996, PhD, Katholieke Universiteit Leuven, ISBN 90–5682-025-7.
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      • M.G. Bellanger . (1987) Adaptive digital filters and signal analysis.
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