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Decreasing the minimal sample period for recursive filters implemented using distributed arithmetic

机译:减少使用分布式算法实现的递归滤波器的最小采样周期

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For distributed arithmetic the latency is proportional to the maximal number of fractional bits for any coefficient. When implementing recursive filters this is a disadvantage as the resulting minimal sample period may be longer compared with an implementation using separate multiplications and additions. In this paper we propose a method to decrease the latency for inputs where the corresponding coefficient has less fractional bits than the maximal of that distributed arithmetic unit. Further, we show how to utilize this technique to decrease the minimal sample period (iteration period) and how to schedule the distributed arithmetic operations to achieve this lower bound.
机译:对于分布式算术,等待时间与任何系数的小数位数的最大数量成正比。当实现递归滤波器时,这是一个缺点,因为与使用单独的乘法和加法的实现相比,所得到的最小采样周期可能更长。在本文中,我们提出了一种减少输入延迟的方法,其中相应系数的分数位比该分布式算术单元的最大值小。此外,我们展示了如何利用该技术来减少最小采样周期(迭代周期),以及如何调度分布式算术运算以实现此下限。

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