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Design and Factorization of Two-Channel Perfect Reconstruction Filter Banks with Causal-Stable IIR Filters

机译:具有因果稳定IIR滤波器的两通道完美重构滤波器组的设计和分解

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摘要

In this paper, new design and factorization methods of two-channel perfect reconstruction (PR) filter banks (FBs) with casual-stable IIR filters are introduced. The polyphase components of the analysis filters are assumed to have an identical denominator in order to simplify the PR condition. A modified model reduction is employed to derive a nearly PR causal-stable IIR FB as the initial guess to obtain a PR IIR FB from a PR FIR FB. To obtain high quality PR FIR FBs for carrying out model reduction, cosine-rolloff FIR filters are used as the initial guess to a nonlinear optimization software for solving to the PR solution. A factorization based on the lifting scheme is proposed to convert the IIR FB so obtained to a structurally PR system. The arithmetic complexity of this FB, after factorization, can be reduced asymptotically by a factor of two. Multiplier-less IIR FB can be obtained by replacing the lifting coefficients with the canonical signal digitals (CSD) or sum of powers of two (SOPOT) coefficients.
机译:本文介绍了具有稳态IIR滤波器的两通道完美重构(PR)滤波器组(FB)的新设计和分解方法。为了简化PR条件,假设分析滤波器的多相分量具有相同的分母。采用改进的模型约简来推导几乎PR因果稳定的IIR FB作为初始猜测,以便从PR FIR FB获得PR IIR FB。为了获得高质量的PR FIR FB进行模型简化,将余弦衰减FIR滤波器用作非线性优化软件的初始猜测,以求解PR解决方案。提出了基于提升方案的因式分解,将如此获得的IIR FB转换为结构上的PR系统。分解后,该FB的算术复杂度可以渐近降低2倍。通过用标准信号数字(CSD)或两个系数的乘方之和代替提升系数,可以获得无倍数IIR FB。

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