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Automatic Synthesis of Reversible Logic Circuit Based on Genetic Algorithm

机译:基于遗传算法的可逆逻辑电路自动综合

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The reversible logic circuits (RLC) are a sort of novel circuits which can avoid the information loss and energy dissipation by implementing the reversible logic operations. RLC prohibit the feedback and don't have the fan-out, so the synthesis methods of RLC are very different from the existing irreversible logic circuits. In this paper, evolutionary design techniques are applied to the synthesis of RLC, and then an automatic synthesis approach of RLC based on genetic algorithm is proposed. Firstly, some appropriate reversible logic gates are chosen as the building-blocks, and a computational array model is built for the synthesis of RLC. According to the array model, the synthesis problems are modeled as the constrained multi-objective optimization problems which are converted into their single-objective equivalents by the weighted sum of objective functions. Then, the single-objective equivalents are solved by a specialized genetic algorithm. The experimental results verify the capability of automatic synthesis of the proposed approach, and show that the proposed approach is feasible and effective.
机译:可逆逻辑电路(RLC)是一种新颖的电路,可通过实现可逆逻辑操作来避免信息丢失和能量消耗。由于RLC禁止反馈并且没有扇出,因此RLC的合成方法与现有的不可逆逻辑电路有很大不同。本文将进化设计技术应用于RLC的合成,提出了一种基于遗传算法的RLC自动合成方法。首先,选择一些合适的可逆逻辑门作为构建模块,并建立一个计算阵列模型用于RLC的综合。根据阵列模型,将综合问题建模为受约束的多目标优化问题,并通过目标函数的加权总和将其转化为单目标等效项。然后,通过专门的遗传算法求解单目标等价物。实验结果验证了该方法自动综合的能力,表明该方法是可行和有效的。

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