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The weights areupdated by LMA until the threshold error is achieved.
Asymptotic stability of the transverse and longitudinal dynamics and the velocity tracking error is achieved.
Unless the non-uniform samples capture the behavior of these short-duration transients, a larger recovery error is achieved.
The correlation between real data and estimated values is over 90%, while the mean square error is achieved around 0.4.
Ascan be seen, the minimal error is achieved in Co-doped ZnO thin films and limited to0% in all concentrations.
Then, the coefficient in the prediction equation is continuously adjusted until the lowest possible error is achieved.
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The smallest training error was achieved with radial basis networks.
A 1.9 h reduction in timing error was achieved using GARR as input rather than RGO.
A network of three neurons was trained repeatedly on multiple examples until a minimal error was achieved.
The smallest average percentage error was achieved by method 4 when using coronal ICAs and the smallest variance in percentage error by method 4 when using sagittal ICAs.
The present calculations used 50 & 90 million histories and 0.354% & 0.312% RMS statistical pin power percent error were achieved for the three-dimensional configurations.
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