基于有序特征值矩阵的对称变量检测算法

An algorithm for Identifying Symmetric Variables Based on the Order Eigenvalues Matrix

为简化布尔函数中12类对称变量的检测过程,提出了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实现对称变量的快速检测。应用结果表明,与现有方法相比,新方法在适用的布尔函数变量数、检测类型和检测过程的复杂度方面是最优算法。

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. By analyzing the constraint conditions of the order eigenvalues matrixs for 12 types of symmetric variables, the algorithm for identifying symmetric variables of Boolean function is proposed. The application results show that,compared with traditional methods the new algorithm is an optimal detection method in tems of applicability of the number of logical variables, detection types, and complexity of the identification process.