Hanoch Lev-Ari

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The signal subspace approach for speech enhancement is extended to colored-noise processes. Explicit forms for the linear time-domain- and spectral-domain-constrained estimators are presented. These estimators minimize the average signal distortion power for given constraints on the residual noise power in the time and spectral domains, respectively.(More)
We present a brief overview of the speech enhancement problem for wide-band noise sources that are not correlated with the speech signal. Our main focus is on the spectral subtraction approach and some of its derivatives in the forms of linear and non-linear minimum mean square error estimators. For the linear case, we review the signal subspace approach,(More)
A universal characterization of maximum-entropy covariances for multidimensional signals is presented. We show that the maximum-entropy extension of an arbitrary partial covariance of a nonstationary multidimensional signal always has what we call a banded inverse, i.e., the inverse is sparse and has the same support as the given partial covariance. We(More)
We present a computationally-efficient matrix-vector expression for the solution of a matrix linear least squares problem that arises in multistatic antenna array processing. Our derivation relies on an explicit new relation between Kronecker, Khatri-Rao and Schur-Hadamard matrix products, which involves a selection matrix (i.e., a subset of the columns of(More)