大变量多输出逻辑函数实质项识别算法

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.

Essential Prime Identification Algorithm for Large Variable Multi-output Logic Functions

This paper analyzes algorithm of Espresso. Based on judging macrocosm, it presents an algorithm of identification about multi-input multi-output logic functions essential primes and complete redundancies and relative redundancies. It calculates cofactor of multi-input multi-output logic functions to judge macrocosm, identifies essential primes and complete redundancies and relative redundancies according by result of judging macrocosm, then forms club of essential primes and complete redundancies and relative redundancies. It completes optimization identification software design of multi-input multi-output logic functions about two-level SOE It is confined that the max-input variables are 128, the max-output variables are 256, the sum of max-input-output variables are 300, the max-input products are 20 000, and it successfully overpasses testing of Benchmark based on computer of Pentium 1.8GHz and 512MB memory.