By Karim Helwani
This ebook treats the subject of extending the adaptive filtering concept within the context of big multichannel structures by way of taking into consideration a priori wisdom of the underlying approach or sign. the start line is exploiting the sparseness in acoustic multichannel approach so one can remedy 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 common sparse representations of acoustic MIMO systems in sign or method established rework domains. Efficient adaptive filtering algorithms in the remodel domain names are provided and the relation among the sign- and the system-based sparse representations is emphasised. moreover, the e-book offers a unique method of spatially preprocess the loudspeaker signs in a full-duplex verbal exchange method. the belief of the preprocessing is to avoid the echoes from being captured via the microphone array on the way to aid the AEC method. The preprocessing degree 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 removal residual echoes. As first of its sort, it extracts the near-end sign from the microphone sign with a distortionless constraint and with no requiring a double-talk detector.
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Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations (T-Labs Series in Telecommunication Services) by Karim Helwani