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Adaptive recursive deconvolution and adaptive noise cancellation

机译:自适应递归反卷积和自适应噪声消除

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In this paper we apply a recursive deconvolution method to active noise cancellation (ANC) in a linear system: the observation of the output of a linear system of relative degree one, read at discrete time instants, is fed to a deconvolution algorithm which identifies the disturbance (with the delay of one step). This information is used in order to reduce the effect of the disturbance itself. Deconvolution being an ill posed problem, a regularization parameter is to be introduced. The choice of the value of the parameter is a delicate issue. We show that, when studying ANC, the discrepancy principle (applied recursively) is a feasible method for the choice of the parameter.
机译:在本文中,我们将递归反卷积方法应用于线性系统中的主动噪声消除(ANC):在离散时间点读取的相对度为1的线性系统的输出的观测值将馈送到反卷积算法,该算法可识别干扰(延迟一步)。使用此信息是为了减少干扰本身的影响。去卷积是一个不适的问题,将引入正则化参数。参数值的选择是一个微妙的问题。我们表明,在研究ANC时,差异原理(递归应用)是选择参数的可行方法。

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