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Adaptive filtering for non-Gaussian processes

机译:非高斯过程的自适应滤波

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A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulation study, applying both synthetic and real-world signals, shows that the proposed method has overall better robustness performance, in terms of modeling error, compared with state-of-the-art robust filtering methods. A remarkable property of the proposed method is that it can handle double-talk in the acoustical echo-cancellation problem.
机译:提出了一种基于非线性幅度变换的新的随机梯度鲁棒滤波方法。该方法不需要先验的输入信号特性知识,并且对信号分布并对信号的实用性不敏感。一种仿真研究,应用合成和真实信号,表明该方法在建模误差方面具有更好的稳健性能,与最先进的鲁棒滤波方法相比。所提出的方法的显着性质是它可以在声学回声消除问题中处理双口谈。

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