一种用于盲反卷积的滤波器设计,从复杂耦合的SRAM余量变化中解耦未知RDF/RTN因子

H. Yamauchi, Worawit Somha
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引用次数: 4

摘要

本文提出了一种盲反卷积技术,用于解耦随机电报噪声(RTN)和随机掺杂波动(RDF)引起的两个变化因子。与非盲反褶积不同,盲反褶积必须同时寻找RTN和RDF的两个未知因子,仅给定关于SRAM总体余量分布的信息。提出了一种新的Richardson-Lucy (R-L)盲反卷积滤波器设计技术。这使得在享受R-L算法的好处的同时,即使在盲反卷积中也避免了固有的陷阱或振铃错误。仅在300个迭代周期内,RDF和RTN的盲反褶积相对误差降低到1%以下。这比传统的短400倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A filter design for blind deconvolution to decouple unknown RDF/RTN factors from complexly coupled SRAM margin variations
This paper demonstrates a blind deconvolution technique for decoupling the two variation factors caused by the Random Telegraph Noise (RTN) and the Random Dopant Fluctuation (RDF). Unlike the non-blind deconvolution, the blind deconvolution has to seek both of the two unknown factors for RTN and RDF simultaneously, given only the information about the overall SRAM margin distribution. This paper proposes a new filter design technique for the Richardson-Lucy (R-L) blind deconvolutions. This allows to enjoy the benefits of the R-L algorithm while avoiding the inherent pitfall or ringing errors even in the blind deconvolution. The relative errors of the blind-deconvolution for RDF and RTN are reduced to less than 1% within only 300-iteration cycles. This is 400-times shorter than the conventional one.
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