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Uniform FIR approximation of causal Wiener filters, with applications to causal coherence

机译:因果维纳滤波器的均匀FIR逼近,并应用于因果相干

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Leveraging the relationship between Wiener filtering and the coherence function, a version of coherence is defined that captures the causal relationship between WSS processes. This causal coherence is interpreted in a modeling context and used to demonstrate what a frequency dependent measure for causality both can and cannot represent. To understand how well frequency dependent causal coherence spectra can be estimated with finite order approximations, the convergence of FIR causal Wiener filters to the full IIR causal Wiener filter is investigated as filter length goes to infinity. The main results prove L~p convergence of the frequency responses for p = 1,2, ∞ under certain H61der continuity conditions on the power spectra, as well as give asymptotic upper bounds for the convergence error. As a corollary, under the same conditions, the uniform convergence of the power spectra of AR approximations is shown as model order goes to infinity.
机译:利用维纳滤波和相干函数之间的关系,定义了一个相干版本来捕获WSS进程之间的因果关系。此因果一致性在建模上下文中得到解释,并用于证明因果关系的频率相关度量既可以表示也不能表示。为了了解如何用有限阶近似估计频率相关的因果相干谱,当滤波器长度达到无穷大时,研究了FIR因果维纳滤波器到完整IIR因果维纳滤波器的收敛性。主要结果证明了在功率谱上某些H61der连续性条件下,p = 1,2,∞的频率响应的L〜p收敛,并给出了收敛误差的渐近上限。作为推论,在相同条件下,随着模型阶数达到无穷大,AR近似的功率谱的均匀收敛被显示出来。

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