1. 复旦大学专用集成电路与系统国家重点实验室,上海,201203
2. Department of Electrical and Computer Engineering,University of Windsor,Ontario,Canada,N9B 3P4
3. 复旦大学专用集成电路与系统国家重点实验室上海,201203
4. Department of Electrical and Computer EngineeringUniversity of WindsorOntarioCanada,N9B 3P4
纸质出版:2007
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吴一品, 周 锋, 陈春鸿, 等. 考虑时间相关性的功耗估计熵算法[J]. 电子学报, 2007,35(5):933-936.
WU Yi-pin, ZHOU Feng, CHEN Chun-hong, et al. An Improved Entropy to Estimate Power for Considering Temporal Correlation at High-Level[J]. Acta Electronica Sinica, 2007, 35(5): 933-936.
熵估计是一种在高层次估计功耗的方法
但已经提出的熵算法无法考虑输入信号在时间上的相关性.本文提出了改进熵的概念
在传统熵中加入条件翻转因子
使改进后的熵能够有效估计时间上有相互关联性的信号的翻转率.理论证明和大量BENCHMARK实验结果都表明我们提出的改进熵算法具有合理性和可靠性.
The traditional entropy is an efficient method for high-level power estimation
but it doesn’t work when the input signals are temporal correlated
as is always the case for video and audio streams.This paper aims at this problem.We put forward a new definition of entropy.With the help of the conditional transition probabilities
the proposed algorithm can bring us the estimations with adequate accuracy for temporal correlated inputs.The theoretical proofs and the BENCHMARK experimental results verify the efficiency of our algorithm.
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