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The primary path error count algorithm is given as follows.
Idle Path error count algorithm is given as follows.
Besides, a straightforward analytical model to estimate the path error probability is presented.
MMDSR uses an analytical model to estimate the path error probability.
Table 2 Experimental data for quality-aware SCTP path error detection mechanism.
When the path error type is a short-term error with high frequency, the existing SCTP mechanism cannot work successfully.
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This mechanism can only detect continuous long-term path errors.
Measured robot paths are applied to the compensation unit and analyzed with respect to the reduction of robot path errors.
In order to compare learning, exponential curves were then least-square fitted to the hand path errors for each subject in order to compare learning rates as a function of trial number (using Matlab® R14 function lsqcurvefit).
Each path was man checked to handle axon path errors arising from local hot spots in the image stack.
Therefore the amount of non-common path errors is reduced and no additional chromatic aberrations are introduced.
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