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Source separation of baseband signals in Post-Nonlinear mixtures

机译:后非线性混合中的基带信号源分离

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Usually, source separation in Post-Nonlinear (PNL) models is achieved via one-stage methods, i.e. the two parts (linear and nonlinear) of a PNL model are dealt with at the same time. However, recent works have shown that the development of two-stage techniques may simplify the problem. Indeed, if the nonlinear stage can be compensated separately, then, in a second moment, one can make use of the well-established source separation algorithms for the linear case. Motivated by that, we propose in this work a novel two-stage PNL method relying on the assumption that the sources are bandlimited signals. In the development of our method, special care is taken in order to make it as robust as possible to noise. Simulation results attest the effectiveness of the proposal.
机译:通常,后非线性(PNL)模型中的源分离是通过一级方法实现的,即,PNL模型的两个部分(线性和非线性)要同时处理。但是,最近的工作表明,两阶段技术的发展可以简化该问题。的确,如果非线性阶段可以分别得到补偿,那么在第二时刻,对于线性情况,可以利用公认的源分离算法。出于此目的,我们在这项工作中提出了一种新颖的两阶段PNL方法,该方法基于以下假设:源是带宽受限的信号。在我们方法的开发中,要特别注意以使其对噪声尽可能强。仿真结果证明了该建议的有效性。

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