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However, this method cannot guarantee optimal levels of throughput.
The HLPC method cannot guarantee the stability of the estimated AR model.
However, this method cannot guarantee that every device outside the ZC's neighbourhood belongs to a certain cluster.
Yet, this method cannot guarantee interference-free operation since the femtocell must also provide complete coverage in the user's home.
Furthermore, since we cope with the coefficients separately, this method cannot guarantee the homogeneity in the resultant fused image.
Although the proposed method cannot guarantee to achieve the same performance as the GLRT-based detector in the general case, experimental results show that the BER performance of the method is very close to that of the GLRT when (the signal-to-noise ratio (SNR) gap is less than dB).
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However, current methods cannot guarantee that the selected subset could represent the global distribution of the entire dataset.
However, these methods cannot guarantee that the performance function value is smaller than that of previous point.
This method requires a large measurement time especially for wide band frequency measurements; therefore such methods cannot guarantee reliable results in open area.
An important issue is that most of corresponding mathematical optimization models are non-convex and involve multiple criteria; hence, conventional convex optimization methods cannot guarantee finding global (Pareto) optimal solutions.
However, indirect methods cannot guarantee correct results in all cases.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com