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在对Espresso算法进行分析改进的基础上,提出了一种基于全域识别的多输入多输出逻辑函数实质本源项、完全冗余项和相对冗余项生成算法,该算法通过对基于积项表示的多输入多输出逻辑函数的余因子计算来进行全域判断,根据全域判断结果来识别实质本源项、完全冗余项和相对冗余项,从而构成实质本源项集合、完全冗余项集合和相对冗余项集合。对基于二级SOP型的多输入多输出逻辑函数设计了多输入多输出逻辑函数优化识别软件系统,允许的最大输入变量数为128、最大输出变量数为256、最大输入输出变量总和为300、最大输入积项数为20 000。软件系统在Pentium 1.8GHz、512MB内存的计算机上通过了Benchmark例题的测试。
Based on the analysis and improvement of Espresso algorithm, this paper proposes a new algorithm based on global recognition, which is the real source item, the complete redundancy item and the relative redundant item generation algorithm of multiple input multiple output logic function. Multiple input and multiple output logic functions to make global judgments, and according to the result of global judgment, to identify the substantial source items, the complete redundancy items and the relative redundancy items, so as to form the substantial source item sets, the complete redundant item sets and the relative redundancy Remaining collection. The multi-input and multi-output logic function optimization identification software system based on the second-order SOP type multi-input multi-output logic function is designed. The maximum number of input variables allowed is 128, the maximum number of output variables is 256, the maximum sum of input and output variables is 300, The maximum number of input product is 20,000. The software system passed Benchmark example tests on a Pentium 1.8GHz, 512MB memory computer.