Abstract:Sparse Bayesian learning (SBL) has been extended to estimate acoustic channel impulse responses (CIRs) at low frequencies, where matched filter (MF)-based CIR estimation suffers from low resolution due to a limited frequency band. In this study, the extended SBL was developed to account for nonuniform noise power in a signal model for the CIR via a formulation that considers inconsistent noise and multiple measurements, which cannot be handled in the conventional SBL. The extended SBL is applied to simulated a… Show more
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