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Two-Step Optimization Approach for the Design of Multiplierless Linear-Phase FIR Filters

机译:无乘数线性FIR滤波器设计的两步优化方法

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Deterministic tree search algorithms for the design of multiplierless linear phase finite impulse response filters are generally time consuming. Many researches therefore focus on how to restrict the number of discrete values assigned to each coefficient during a tree search. In this paper, a two-step tree search algorithm is proposed. In the first step, a polynomial-time tree search algorithm where each coefficient is fixed to a single one discrete value is introduced. Since the synthesis of large coefficients is dominant in the hardware cost over small coefficients, in the second step optimization, the small coefficients obtained in the first step is kept unaltered and the large coefficients are further divided into several groups and the coefficients are optimized group by group alternatingly. Such a two-step search strategy maximally utilizes the limited computational resources and can achieve lower hardware cost design in a shorter design time, compared with existing algorithms.
机译:用于设计无乘法器线性相位有限脉冲响应滤波器的确定性树搜索算法通常很耗时。因此,许多研究集中于如何在树搜索期间限制分配给每个系数的离散值的数量。本文提出了一种两步树搜索算法。第一步,引入多项式时间树搜索算法,其中每个系数都固定为单个一个离散值。由于大系数的合成在硬件成本上占主导地位而不是小系数,因此在第二步优化中,第一步中获得的小系数保持不变,并且将大系数进一步划分为几组,然后逐个对系数进行优化交替分组。与现有算法相比,这种两步搜索策略最大程度地利用了有限的计算资源,并且可以在较短的设计时间内实现较低的硬件成本设计。

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