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The use of a single hard threshold value is precisely the source of important segmentation errors in many scenarios like noisy images or uneven illumination.
We have used r = 0.6 as a "hard" threshold value for the CC.
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(iii) Hard threshold using as threshold value.
Hard threshold using as threshold value.
Recently, k t FASTER method has been proposed on similar lines that recovers fMRI signal via hard thresholding of singular values of low-rank data matrix X in the CS framework [11].
Key parameters including Lagrange multipliers (λs, λp), penalty factor μ of SALSA and hard threshold ε are studied to determine their optimal value ranges.
Commonly, this is achieved through the application of a hard threshold, keeping only edges whose weight exceeds a predetermined value.
Determination of optimal resistance threshold value that minimizes the overall error rate (hard and soft) for MLC PRAM.
Finally, the decision engine gives the final result by comparing the estimated value to the threshold value according to (10), which provides a hard decision output of the detector.
A common method is to simply apply a hard threshold, keeping only those edges whose weight exceeds some predetermined value.
We analyze the effect of threshold resistance on the total error rate (combination of hard and soft error rates) and show that there is an optimal threshold value for a given data storage time and number of programming cycles.
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