基于新型融合加法器的随机DFT算法设计

针对目前随机运算结构在多级运算的过程中，运算精度损失严重的问题，提出一种全新的融合随机加法运算结构，并通过一种新的数学分析方法:超几何分解来对此结构进行原理分析，证明了这种加法结构比传统加法结构具有更高的运算精度。 采用融合加法器完成了一种随机离散傅里叶变换算法的架构设计，成功将随机运算的多种优点引入到离散傅里叶变换（DFT）处理领域，并在应用中证明了新型融合随机加法器的有效性。 

Design of High Tolerance DFT Algorithm Based on a Novel Fusion Adder

In order to increase computing accuracy in multiple stages computing architecture, a novel stochastic fusion adder has been proposed, in which a new mathematical method, named hypergeometric decomposition, was developed to analyze the property of the proposed adder. It is shown that the proposed algorithm has much higher precision than the traditional one. By designing a stochastic DFT architecture based on this enhanced stochastic adder, all the advantages of stochastic computing were merged into DFT computing domain, and the DFT implementation also proves the successful design of this novel fusion stochastic adder.