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Structural Properties of the Wiener Filter—Stability, Smoothness Properties, and FIR Approximation Behavior

机译:维纳滤波器的结构特性-稳定性,平滑度和FIR近似行为

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Any Wiener filter can be interpreted as a cascade of a whitening and estimation filter. The whitening filter is determined due to the spectral factorization of the spectral density of the input signal. For the calculation of the estimation filter the spectral factorization as well as the so called plus-operator is needed. This correspondence investigates in detail the behavior of these two operations and studies the corresponding properties of both filters. Then the practical consequences for the overall Wiener Filter are discussed. It is shown that if the given spectral densities are smooth (HÖlder continuous) functions, the resulting Wiener filter will always be stable and can be approximated arbitrarily well by a finite impulse response (FIR) filter. Moreover, the smoothness of the spectral densities characterizes how fast the FIR filter approximates the desired filter characteristic, and the correspondence gives a class of approximation polynomials which actually achieves the optimal approximation behavior. On the other hand, if the spectral densities are continuous, but not HÖlder continuous, the resulting Wiener filter may not be stable.
机译:任何维纳滤波器都可以解释为白化和估计滤波器的级联。由于输入信号频谱密度的频谱分解而确定了白化滤波器。为了计算估计滤波器,需要频谱分解以及所谓的正运算符。该对应关系详细研究了这两个操作的行为,并研究了两个过滤器的相应属性。然后讨论了整个维纳滤波器的实际后果。结果表明,如果给定的光谱密度是平滑的(Holder连续)函数,则所得的维纳滤波器将始终保持稳定,并且可以通过有限脉冲响应(FIR)滤波器任意近似地近似。此外,频谱密度的平滑度表征了FIR滤波器逼近所需滤波器特性的速度,并且该对应关系给出了一类逼近多项式,该逼近多项式实际上实现了最佳逼近行为。另一方面,如果光谱密度是连续的,但不是HÖlder连续的,则所得的维纳滤波器可能会不稳定。

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