By Karim Helwani
This e-book treats the subject of extending the adaptive filtering thought within the context of huge multichannel structures via making an allowance for a priori wisdom of the underlying process or sign. the place to begin is exploiting the sparseness in acoustic multichannel process so that it will resolve the non-uniqueness challenge with a good set of rules for adaptive filtering that doesn't require any amendment of the loudspeaker signals.
The booklet discusses intimately the derivation of normal sparse representations of acoustic MIMO systems in sign or procedure 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 ebook offers a singular method of spatially preprocess the loudspeaker signs in a full-duplex conversation approach. the assumption of the preprocessing is to avoid the echoes from being captured through the microphone array that allows you to aid the AEC approach. The preprocessing level is given as an exemplarily application of a singular unified framework for the synthesis of sound figures. Finally, a multichannel process for the acoustic echo suppression is presented that can be utilized as a postprocessing degree for elimination residual echoes. As first of its type, 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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Extra 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