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A novel design and implementation technique for low complexity variable digital filters using multi-objective artificial bee colony optimization and a minimal spanning tree approach

机译:利用多目标人工蜂群优化和最小生成树方法的低复杂度可变数字滤波器的新设计和实现技术

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摘要

Farrow structure in canonic signed digit (CSD) space is an efficient approach for the design of real-time tunable finite precision variable digital filters (VDFs). A novel design method for Farrow structure based VDFs in CSD space with reduced hardware complexity is proposed in this paper. The design approach makes use of the multi-objective artificial bee colony (MOABC) optimization algorithm with an integer search space to find the optimal Farrow sub-filter coefficients. Further, a novel low complexity implementation approach for the finite precision VDF using a minimal spanning tree approach is also proposed. The minimal spanning tree approach deploys the shift inclusive differential coefficients (SIDCs) and the different shifted SIDCs with common sub-expression elimination (CSE) to optimize the multiple constant multiplications involved in the filter realization. The attractive feature of our proposed method using MOABC and SIDCs with CSE lies in the increased hardware complexity reduction of the VDFs, compared to the existing methods, which in turn reduces the hardware resource utilization and power consumption drastically compared to the continuous coefficient VDFs. The hardware implementation of the VDF using the proposed method has also been done using Xilinx ISE to analyse the reduction in the hardware complexity and dynamic power.
机译:规范符号数字(CSD)空间中的Farrow结构是一种设计实时可调有限精度可变数字滤波器(VDF)的有效方法。提出了一种新的基于Farrow结构的CSD空间中VDF的设计方法,该方法降低了硬件复杂度。该设计方法利用具有整数搜索空间的多目标人工蜂群(MOABC)优化算法来找到最佳Farrow子滤波器系数。此外,还提出了一种使用最小生成树方法的有限精度VDF的新型低复杂度实现方法。最小生成树方法使用公共子表达式消除(CSE)部署移位包含差分系数(SIDC)和不同移位的SIDC,以优化滤波器实现中涉及的多个常数乘法。我们提出的将MOABC和SIDC与CSE一起使用的方法的吸引人之处在于,与现有方法相比,VDF的硬件复杂性降低了更多,与连续系数VDF相比,这又大大降低了硬件资源利用率和功耗。使用Xilinx ISE还完成了使用提出的方法对VDF的硬件实现,以分析硬件复杂度和动态功耗的降低。

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