【摘要】 为了提高在信息论基础上的逻辑电路面积和功耗分析方法的估计精度,在传统输出信息熵估计理论基础上,提出了利用翻转信息熵进行电路实现复杂度和面积估计的理论方法。概率的方法被用于对组合逻辑电路的输入输出信号翻转行为的相关和相似进行量化分析。在此基础上实现了翻转信息熵面积估计算法,对随机生成的大量电路和标准benchmark电路进行的实验结果表明,该方法带来了至少3%左右的估计精度改善。更多还原

【Abstract】 The estimation precision of analytical methods for logic circuits using information theory was improved using a new area estimation model with transition information entropy. The method was based on an analysis of the relationships and similar probabilities of the input and output signals of logic circuits. Probability methods were used to evaluate the similarities and relationships. The area estimation algorithm with transition entropy was applied to various random circuits and benchmark circuits, and the experimental results have at least 3% better estimation precision for logic circuits with m inputs and one output.更多还原