Steady-state performance limitations of subband adaptive filters
Steady-state performance limitations of subband adaptive filters
复制标题
子带自适应滤波器的稳态性能限制
DOI：
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发表时间：
2001
影响因子：
5.4
通讯作者：
R. Rabenstein
中科院分区：
文献类型：
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作者：
Stephan Weiss;A. Stenger;R. Stewart;R. Rabenstein
用于子带自适应滤波（SAF）的非完美滤波器组是已知的，对这种系统的稳态性能施加限制。在本文中，我们量化的最小均方误差（MMSE）和准确性，整个SAF系统可以模拟一个未知的系统，它是用来识别。首先，在MMSE限制的情况下，基于混叠信号分量的功率谱密度描述来评估误差，所述功率谱密度描述可通过我们导出的子带信号的源模型来访问。MMSE的近似值可以嵌入到信号混叠比（SAR）中，SAR是自适应滤波可以降低误差功率的一个因素。简化后，SAR仅取决于滤波器组。其次，在建模的情况下，我们将SAF系统的精度与完美重建中的滤波器组失配联系起来。当使用调制滤波器组时，误差限制（MMSE和不准确性）都可以与原型相关联。我们明确推导出广义DFT调制滤波器组，并证明了分析误差限制和近似的一些例子的有效性，从而分析预测的误差量的限制比较有利的模拟。
Nonperfect filterbanks used for subband adaptive filtering (SAF) are known to impose limitations on the steady-state performance of such systems. In this paper, we quantify the minimum mean-square error (MMSE) and the accuracy with which the overall SAF system can model an unknown system that it is set to identify. First, in case of MMSE limits, the error is evaluated based on a power spectral density description of aliased signal components, which is accessible via a source model for the subband signals that we derive. Approximations of the MMSE can be embedded in a signal-to-alias ratio (SAR), which is a factor by which the error power can be reduced by adaptive filtering. With simplifications, SAR only depends on the filterbanks. Second, in case of modeling, we link the accuracy of the SAF system to the filterbank mismatch in perfect reconstruction. When using modulated filterbanks, both error limits-MMSE and inaccuracy-can be linked to the prototype. We explicitly derive this for generalized DFT modulated filterbanks and demonstrate the validity of the analytical error limits and their approximations for a number of examples, whereby the analytically predicted limits of error quantities compare favorably with simulations.