An improved method for blind separation of complex-valued signals via joint diagonalization

The problem of blind separation of complex-valued signals via joint diagonalization of a set of non-unitary target matrices is addressed in this paper. An improved blind source separation (BSS) algorithm is developed based on minimization of the Frobenius-norm formulation of the approximate joint diagonalization problem by using a multiplicative update. Such minimization yields a strictly diagonally-dominant updated matrix at each iteration. With relaxing some constraints on the target matrices, the improved BSS algorithm allows for extended applications. The behavior of the improved BSS algorithm is demonstrated by computer simulation results in comparison with some representative BSS algorithms.