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A Combined Optimization Method of Finite Wordlength FIR Filters

机译:有限字长FIR滤波器的组合优化方法

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FIR filters are very important in digital system design. The fix-point hardware implementation of FIR filters has the advantages of low cost and high performance. But this kind of hardware implementation introduces the unavoidable quantization error. In this paper, we present a combined method of GA and the local-search to optimize the coefficients of finite wordlength FIR filters. The search ability of GA and the efficiency of the local-search method are combined, and the genetic operators are selected carefully. The experiment result shows that the quantization error of the finite wordlength FIR filters is suppressed and within limited iterations, the method is evidently better than the simple GA method in terms of the average convergence performance.
机译:FIR滤波器在数字系统设计中非常重要。 FIR滤波器的定点硬件实现具有低成本和高性能的优点。但是这种硬件实现引入了不可避免的量化误差。在本文中,我们提出了一种结合遗传算法和局部搜索的方法来优化有限字长FIR滤波器的系数。遗传算法的搜索能力和局部搜索方法的效率相结合,并仔细选择了遗传算子。实验结果表明,有限字长FIR滤波器的量化误差得到了抑制,并且在有限的迭代内,该方法在平均收敛性能方面明显优于单纯的GA方法。

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