By Karim Helwani
This booklet treats the subject of extending the adaptive filtering concept within the context of big multichannel structures through taking into consideration a priori wisdom of the underlying process or sign. the place to begin is exploiting the sparseness in acoustic multichannel procedure to be able to resolve the non-uniqueness challenge with an effective set of rules for adaptive filtering that doesn't require any amendment of the loudspeaker signals.
The e-book discusses intimately the derivation of common sparse representations of acoustic MIMO systems in sign or process established remodel domains. Efficient adaptive filtering algorithms in the rework domain names are offered and the relation among the sign- and the system-based sparse representations is emphasised. additionally, the e-book provides a singular method of spatially preprocess the loudspeaker signs in a full-duplex verbal exchange procedure. the belief of the preprocessing is to avoid the echoes from being captured by way of the microphone array which will aid the AEC procedure. The preprocessing degree is given as an exemplarily application of a singular unified framework for the synthesis of sound figures. Finally, a multichannel approach for the acoustic echo suppression is presented that can be utilized as a postprocessing degree for elimination residual echoes. As first of its sort, it extracts the near-end sign from the microphone sign with a distortionless constraint and with out requiring a double-talk detector.
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Additional info for Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations (T-Labs Series in Telecommunication Services)
Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations (T-Labs Series in Telecommunication Services) by Karim Helwani