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GrC-based statistic optimization algorithm for big truth table

机译:基于GrC的大真值表统计优化算法

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Truth table optimization is of great importance for simplification of combinational logic circuits. In this paper, Granular Computing (GrC) and statistic methods are combined to convert traditional big truth table optimization problem into the minimal rule discovery of the logic information system. The proposed method is the improvements of our former work. The possible solutions were searched in different knowledge spaces under different granularity, based on which the statistical parallel optimization algorithm for big truth table was developed. Light-emitting diode (LED) digital display was applied to illustrate the algorithm in detail. Furthermore, the efficiency and effectiveness of the proposed algorithm have been proved in this paper.
机译:真值表优化对于简化组合逻辑电路非常重要。本文将颗粒计算和统计方法相结合,将传统的大事实表优化问题转化为逻辑信息系统的最小规则发现。所提出的方法是对我们以前工作的改进。在不同的知识空间,不同的粒度下搜索可能的解决方案,在此基础上,开发了大真值表的统计并行优化算法。应用了发光二极管(LED)数字显示器来详细说明该算法。此外,本文证明了该算法的有效性和有效性。

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