A Deconvolution Error Avoidance Technique in Richardson- Lucy Method

نویسندگان

  • Hiroyuki Yamauchi
  • Worawit Somha
چکیده

A deconvolution error avoidance technique in Richardson-Lucy deconvolution (RLdeconv) is proposed, which is used for inversely analysing the SRAM margin variations caused by the Random Telegraph Noise (RTN). The proposed technique reduces the phase difference between the deconvoluted RTN distribution and feedback-gain in the maximum likelihood (MLE) gradient iteration cycles. This avoids an unwanted positive feedback, resulting in a significant decrease in probability of ringing occurrence. The effects of the proposed technique on the deconvolution process are demonstrated. A quicker convergence benefit of the RLdeconv algorithm is also observed. It has been demonstrated that the proposed technique reduces its relative deconvolution errors by 100 times compared with the conventional RL-deconv. This provides an increase in accuracy of the fail-bit-count prediction by over 2-orders of magnitude while accelerating its convergence speed by 33times of the conventional one.

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تاریخ انتشار 2017