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Negative values means the detection time made by the algorithm leads the NGDC detection.
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The implementation of the algorithm led to asymmetric step sizes.
The application of indenter tip geometries diverging from the determined one by the TiGAF algorithm led to significant deviations of the different stress strain characteristics from the nominal ones.
In addition, regardless of the tolerance value, the advanced algorithm leads to the lowest error, followed by the basic algorithm, with no correction being the worst.
Iteratively minimizing the two-norm of (underline {mathbf {e}}_{text {HM}}{ kappa)}) in a gradient-descent manner by an FNLMS algorithm leads to the update rule begin{aligned} hat{underline{mathbf{h}}}^{(p)}{ kappa)} &=mathbf{FW}_{10}mathbf{F}^{{mathrm{H}}}left vphantom{hat{underline{mathbf{h}}}^{(p)}{ kappa-1)} underline{ kappa-1}}}hat{underline{mathbf{h}}}hat{underline{mathbf{h}.
The results of the table raise the following issues during interpretation: First, as expected, applying different cut-off thresholds to the results by a given algorithm leads to a different number of peaks being identified: there is inevitably a trade-off between the number of peaks recovered and the quality of the peaks.
In addition, the advanced algorithm leads to higher similarity than the basic algorithm, regardless of α.
The proposed algorithm leads to better results.
It has been demonstrated that the performance of the resulting electrode configurations developed by the algorithm perform comparably with lead sets that have been suggested using similar data but using a different technique.
The growth and branching processes, performed by the so-called Tom Thumb algorithm, lead thus to the configuration and cloning mechanisms of the systems.
The different sequence of resource allocations produced by different algorithms leads to different resource availability scenarios which implies different probabilities of success in the acceptance a request.
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