基于向量空间方法的非双正交滤波器组完美重构

S. Nalbalwar, S. Joshi, R. Patney
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引用次数: 0

摘要

提出了一种从给定的非PRFB构造PRFB的公式,并使用滤波器组的向量空间框架进行了描述。为了构建PRFB,在子带中插入一个复用器(TMUX)结构,使TMUX的合成和分析部分与给定滤波器组的分析和合成组双正交。TMUX是由变换矩阵表示的。除了PR外,本文的另一个目的是研究和开发非PR TMUX对应的变换矩阵的性质。变换矩阵被分成不同的子块。对于均匀滤波器组(UFB),证明了变换矩阵的每个子块都具有卷积矩阵结构。而在非均匀滤波器组(NUFB)的情况下,表明每个子块都具有由分散的卷积矩阵组成的结构。用离散时间FIR或IIR滤波器实现这些矩阵也在本文中被展示。卷积矩阵的实现涉及线性时不变滤波器,而分散卷积矩阵的实现涉及时变滤波器。在变换矩阵的实现过程中,还发现一些块可以通过使用实现块来导出。通过在子带中插入一个或多个tmux,并与UFB的子信道合并,可以得到给定UFB的NUFB。UFB在UFB的基础上有各种各样的应用,如语音和音频信号的处理,在这些应用中,不均匀的频段划分是很重要的
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Perfect Reconstruction in Non-biorthonormal Filter Banks using Vector Space Approach
A formulation is proposed for construction of PRFB from a given non-PRFB and is described using vector space framework for filter banks. To construct PRFB, a transmultiplexer (TMUX) structure is inserted into the subband such that the synthesis and analysis parts of the TMUX are biorthonormal to analysis and synthesis bank of the given filter bank. The TMUX is a represented by transformation matrix. In addition to PR, in this paper, another objective is to study and exploit the properties of transformation matrix corresponding to non-PR TMUX. The transformation matrix is portioned into distinct subblocks. In case of uniform filter bank (UFB) it is shown that each subblock of transformation matrix has convolution matrix structure. Whereas in case of nonuniform filter bank (NUFB) it is shown that each of these subblock has a structure consisting of interspersed convolution matrices. Implementation of these matrices using discrete time FIR or IIR filters are also shown in this paper. It is also shown that implementation of convolution matrices involve linear time invariant filters whereas interspersed convolution matrices involve the time varying filters. During the implementation of transformation matrix it is also found that some of the blocks can be derived by using implemented blocks. By inserting one or more TMUXs in the subbands and merging with subchannels of UFB we can obtained NUFB from given UFB. There are various application of NUFB over UFB such as speech and audio signal processing where nonuniform division of bands is important
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