The complex subband decomposition and its application to the decimation of large adaptive filtering problems
The complex subband decomposition and its application to the decimation of large adaptive filtering problems
复制标题
复子带分解及其在大型自适应滤波问题抽取中的应用
DOI：
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发表时间：
2002
影响因子：
5.4
通讯作者：
N. Ahmadvand
中科院分区：
文献类型：
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作者：
J. Reilly;Matthew R. Wilbur;M. Seibert;N. Ahmadvand
我们证明，在分析和合成滤波器组之间插入对角线系统的近乎完美重建（NPR）M通道滤波器组可用于将L阶有限脉冲响应（FIR）系统分解为M个复杂子带分量，每个分量为L/K阶，其中K是下采样率。这种分解的代价是使用复杂的算术进行子带处理。围绕所提出的滤波器组结构的理论导致了对子带自适应滤波实现的新理解。它还自然地导致无延迟子带自适应滤波器方案。使用分析和合成滤波器上的条件，开发了子带分量及其各自属性的公式。给出了声学回声消除 (AEC) 示例的仿真结果来支持所开发的理论。
We show that a near perfect reconstruction (NPR) M-channel filterbank with a diagonal system inserted between the analysis and synthesis filterbanks may be used to decompose a finite impulse response (FIR) system of order L into M complex subband components, each of order L/K, where K is the downsampling rate. This decomposition is at the expense of using complex arithmetic for the subband processing. The theory surrounding the proposed filterbank structure leads to a new understanding of subbanded adaptive filtering implementations. It also leads naturally to a delayless subbanded adaptive filter scheme. Using conditions on the analysis and synthesis filters, the formulas for the subband components and their respective properties are developed. Simulation results for an acoustic echo cancellation (AEC) example are given to support the developed theory.