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A filter design for blind deconvolution to decouple unknown RDF/RTN factors from complexly coupled SRAM margin variations

机译:用于盲解卷积的滤波器设计,用于将未知的RDF / RTN因素与复杂耦合的SRAM容限变化解耦

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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.
机译:本文演示了一种用于将由随机电报噪声(RTN)和随机掺杂物涨落(RDF)引起的两个变化因子解耦的盲解卷积技术。与非盲卷积不同,盲卷积必须同时寻找RTN和RDF的两个未知因素,而仅给出有关总体SRAM容限分布的信息。本文为理查森-露西(R-L)盲反卷积提出了一种新的滤波器设计技术。这样就可以享受R-L算法的优势,同时避免了固有的陷阱或振铃误差,即使在盲反卷积中也是如此。 RDF和RTN的盲去卷积的相对误差在300个迭代周期内减少到小于1%。这比传统的短400倍。

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