A Joint Diagonalization Method for Convolutive Blind Separation of Nonstationary Sources in the Frequency Domain
نویسندگان
چکیده
A joint diagonalization algorithm for convolutive blind source separation by explicitly exploiting the nonstationarity and second order statistics of signals is proposed. The algorithm incorporates a non-unitary penalty term within the cross-power spectrum based cost function in the frequency domain. This leads to a modification of the search direction of the gradient-based descent algorithm and thereby yields more robust convergence performance. Simulation results show that the algorithm leads to faster speed of convergence, together with a better performance for the separation of the convolved speech signals, in particular in terms of shape preservation and amplitude ambiguity reduction, as compared to Parra’s nonstationary algorithm for convolutive mixtures.
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