In stochastic circuits, major sources of error are correlation errors, soft errors and random fluctuation errors that affect the accuracy and reliability of the circuit. The soft error has the effect of changing the correlation status and in turn changes the probability of numbers leading to the erroneous output. This has serious impact on security and medical systems where highly accurate systems are required. We tackle this problem by introducing the fault-tolerant technique of correlation-sensitive stochastic logic circuits. We develop a framework of Remodelling Correlation(ReCo) for Stochastic Logic Elements; AND, XOR and OR for reliable operation. We present two variants of ReCo models in combinational circuits with contradictory requirements by stating two interesting case studies. The proposed technique selects logic elements and places correction blocks based on a priority-based rule that helps to converge to the desired MSE quickly requiring less hardware area. It is shown that this technique does not alter the reliability of the overall circuit. To demonstrate the practical effectiveness of the proposed framework, contrast stretch operation on a standard image in a noisy environment is studied. A high structural similarity index measure of 92.80 is observed for the output image with the proposed approach compared to the image (with error) 66.43.
翻译:在随机电路中,主要的误差源是相关误差、软误差和随机波动误差,这些误差影响到电路的准确性和可靠性。软误差具有改变关联状态的效果,并反过来改变导致错误输出的数字概率。这对安全和医疗系统产生了严重影响,需要高度精确的系统。我们通过采用对关联敏感随机逻辑电路的误差容忍技术来解决这个问题。我们开发了一个框架,用于模拟随机逻辑元素的互换关系;以及,XOR和OR和OR,用于可靠的操作。我们通过说明两个有趣的案例研究,在组合电路中提出了两个变异的ReCo模型,其要求相互矛盾。拟议技术选择了逻辑元素,并根据优先规则设置了校正区块,这有助于迅速达到理想的MSE要求的硬件区域。我们发现,该技术不会改变整个电路的可靠性。为了证明拟议框架的实际有效性,正在研究在噪音环境中对标准图像进行对比拉伸操作。我们用高结构相似度指数测量了92.80,对产出图像与拟议图像进行比较。