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We consider a particular form of the classical approximate joint diagonalization (AJD) problem, which we call a “sequentially drilled” joint congruence (SeDJoCo) transformation. The problem consists of a set of symmetric real-valued (or Hermitian-symmetric complex-valued) target-matrices. The number of matrices in the set equals their dimension, and the joint diagonality criterion requires that in...
In this paper, we introduce a tensor-based subspace method for solving the blind channel estimation problem in a single-input multiple-output (SIMO) system. Since the measurement data is multidimensional, previously proposed blind channel estimation methods require stacking the multiple dimensions into one highly structured vector and estimate the signal subspace via a singular value decomposition...
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