DocumentCode :
1791518
Title :
Deconvolution algorithm dependencies of estimation errors of RTN effects on subnano-scaled SRAM margin variation
Author :
Yamauchi, Hiroyuki ; Somha, Worawit
Author_Institution :
Inf. Intell. Syst., Fukuoka Inst. of Technol. Wajiro-Higashi, Fukuoka, Japan
fYear :
2014
fDate :
6-8 Oct. 2014
Firstpage :
1
Lastpage :
6
Abstract :
This paper compares the proposed technique with various MATLAB-built-in deconvolution-functions with regard to deconvolution errors, which have a crucial impact in reversing the effects of convolution with Random Telegraph Noise (RTN) on overall SRAM margin variations. The proposed technique successfully circumvents the issue of ringing error thanks to eliminating the need for any operations of differential, division, and maximum-likelihood gradient sequence. This advantage over the MATLAB-built-in deconvolution-functions 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 technique can reduce its cdf errors of the convolution of the deconvoluted-RTN with the Random Dopant Fluctuation (RDF) (i.e. fail-bit-count error) by 101-1016 fold compared with the MATLAB-built-in deconvolution-functions.
Keywords :
SRAM chips; deconvolution; gradient methods; maximum likelihood estimation; MATLAB; RDF; RTN effects; deconvolution algorithm dependencies; estimation errors; fail-bit-count error; maximum-likelihood gradient sequence; random dopant fluctuation; random telegraph noise; subnanoscaled SRAM margin variation; Convolution; Deconvolution; MATLAB; Noise; Probability density function; Random access memory; Resource description framework; Deconvolution; MATLAB-deconvolution function; Random telegraph noise; SRAM margin variation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Very Large Scale Integration (VLSI-SoC), 2014 22nd International Conference on
Conference_Location :
Playa del Carmen
Type :
conf
DOI :
10.1109/VLSI-SoC.2014.7004191
Filename :
7004191
Link To Document :
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