Neural network analysis for the identification of optimal variable orderings in the decomposition of complex logic functions
Neural network analysis for the identification of optimal variable orderings in the decomposition of complex logic functions
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DOI：
10.1049/ip-cdt:20020405
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发表时间：
2002-12
期刊：
影响因子：
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通讯作者：
S. Ngwira;P. Tshabalala
中科院分区：
文献类型：
--
作者：
S. Ngwira;P. Tshabalala
提出了一种人工神经网络分析方法，用于预测能对复杂组合逻辑函数进行有效析取分解的输入变量子集。所获得的子集与对析取分解进行穷举搜索得到的最优排序基本匹配。这些子集显著减少了搜索域中的排序数量。因此，该技术可作为全面穷举搜索算法的预处理器。
An artificial neural network analysis is presented to predict the input variable subsets that give efficient disjunctive decompositions of complex combinatorial logic functions. The subsets obtained match substantially with the optimum orderings from an exhaustive search for disjunctive decompositions. The subsets reveal significantly scaled down numbers of orderings in the search domain. The technique can thus serve as a pre-processor of comprehensive exhaustive search algorithms.