This paper addresses the problem of blind identification of a linear instantaneous overdetermined mixture of quasistationary sources, using a new formulation based on KhatriRao (KR) subspace. A salient feature of this formulation is that it decomposes the blind identification problem into a number of per-source, structurally less complex, blind identification problems. We tackle the per-source problems by developing a specialized alternating projections (AP) algorithm. Remarkably, we prove that AP almost surely converges to a true mixing matrix column in its first iteration, assuming an ideal model condition. Simulation results show that the proposed algorithm yields competitive complexity and performance.
A method to suppress the back lobes of a short leaky-wave antenna by two designed considerations is present in this paper. The right triangular end of the LWA is used to reduce the power reflected backwardly and the linked rectangular is guided the remainder power to the ground. With a short LWA length, the back lobes are suppressed successfully both in simulated and measured results at 4.6 and 4.7 GHz. The differences of the gains between the back lobes and main beams are 13.1 dBi and 7.2 dBi at 4.6 and 4.7 GHz, relatively in the measurements. In contrast to the conventional LWA, the proposed short LWA would rather be useful in scanning systems.
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