含无关项布尔函数的对称变量检测算法

An algorithm for identifying symmetric variables of Boolean function with don't-care-terms

为简化布尔函数中12类对称变量的检测过程,提出了含无关项布尔函数基于最小项展开系数的对称变量检测算法.该算法通过判别布尔函数有序特征值矩阵的约束条件以实现对称变量的快速检测.应用结果表明,与现有方法相比,算法在适用的布尔函数变量数、检测类型、检测含无关项布尔函数和检测过程的复杂度方面表现较优.

To simplify the process for identifying 12 types of symmetric variables in Boolean function,we propose a new symmetry detection algorithm based on minterm expansion of Boolean function with don’t-care-terms.By analyzing the constraint conditions of the order eigenvalues matrixes for 12 types of symmetric variables,the algorithm for identifying symmetric variables of Boolean function with don’t-care-terms is proposed.The results show that,the new algorithm method is superior than the traditional methods in the applicability of the number of logical variables of Boolean function including don’t-care-terms,detection types,and complexity of the identification process.