Abstract—This paper presents a comparative analysis of the Random Telegraph Noise (RTN) deconvolution accuracy between the Richardson-Lucy (R-L) algorithm and the proposed partitioned forward problem based deconvolution means (PFDCV). Unlike the R-L based deconvolution, the proposed technique successfully solves the issue of noise amplification thanks to eliminating any operations of differential and division. This effectiveness has been demonstrated for the first time with applying it to a real analysis for the effects of the RTN on the overall SRAM margin variations. It has been shown that the proposed PFDCV technique can reduce its relative errors of the RTN deconvolution by 1014–fold compared with the cases of the R-L.

Index Terms—Random telegraph noise, fail-bit analysis, static random access memory, deconvolution, richardson-lucy deconvolution.

The authors are with the Information Intelligent System Fukuoka Institute of Technology, 3-30-1, Wajiro-Higashi, Higashi-ku, Fukuoka, Japan (e-mail: bd12002@ bene.fit.ac.jp, yamauchi@fit.ac.jp).

Cite:Worawit Somha and Hiroyuki Yamauchi, "A Comparative Study on RTN Deconvolution of Richardson-Lucy and Proposed Partitioned Means for Analyzing SRAM Fail-Bit Prediction Accuracy," International Journal of Computer and Communication Engineering vol. 3, no. 3, pp. 178-183, 2014.