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A residue to binary converter for the {2n + 2, 2n + 1, 2n} moduli set

机译:{2n + 2,2n + 1,2n}模集的残差二进制转换器

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In this paper, we investigate residue number system (RNS) to decimal conversion for a three moduli set with a common factor. We propose a new RNS to binary converter for the moduli set {2n + 2, 2n + 1, 2n} for any even integer n > 0. First, we demonstrate that for such a moduli set, the computation of the multiplicative inverses can be eliminated. Secondly, we simplify the Chinese Remainder Theorem (CRT) to obtain a reverse conveter that uses mod-n instead of mod-(2n+2)(2n) or mod-2n required by other state of the art equivalent converters. Next, we present a low complexity implementation that does not require explicit use of the modulo operation in the conversion process as it is normally the case in the traditional CRT and other state of the art equivalent converters. In terms of area, our proposal requires four 2:1 adders and 2 multipliers while the best state of the art equivalent converter requires one 3:1 adder, two 2:1 adders, and four multipliers. In terms of critical path delay, our scheme requires 3 additions and 1 multiplication with mod-n operations whereas the best state of the art equivalent converter requires 2 additions and 2 multiplications with mod-2n operations. Consequently, our scheme outperforms state of the art converters in terms of area and delay. Moreover, due to the fact that our scheme operates on smaller magnitude operands, it requires less complex adders and multipliers, which potentially results in even faster and smaller implementations.
机译:在本文中,我们研究了具有公共因子的三模数集的残数系统(RNS)到十进制转换。对于任何偶数n> 0的模数集{2n + 2,2n + 1,2n},我们提出了一种新的RNS到二进制转换器。首先,我们证明对于这种模数集,乘法逆的计算可以是被淘汰。其次,我们简化了中国剩余定理(CRT),以获得使用mod-n而不是其他现有技术等效转换器所需的mod-(2n + 2)(2n)或mod-2n的反向对流器。接下来,我们提出了一种低复杂度的实现方式,它不需要在转换过程中显式使用模运算,而在传统的CRT和其他现有技术等效转换器中通常就是这种情况。就面积而言,我们的建议需要四个2:1加法器和2个乘法器,而最先进的等效转换器需要一个3:1加法器,两个2:1加法器和四个乘法器。就关键路径延迟而言,我们的方案需要3次加法和1次乘以n运算,而最先进的等效转换器需要2次加法和2次乘以mod-2n运算。因此,我们的方案在面积和延迟方面都优于最新的转换器。而且,由于我们的方案在较小量级的操作数上进行操作,因此需要较少复杂的加法器和乘法器,这有可能导致更快,更小的实现。

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