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Then, there's the problem of sample bias.
The method uses the MCMC to solve the problem of sample impoverishment in UPF algorithm.
Resampling operation solves degeneracy to some extent, but it results in the problem of sample impoverishment.
A further problem mentioned above is the problem of sample size.
Theoretically, the problem of sample impoverishment can be avoided if we are able to resample from a continuous distribution rather than a discrete one.
This paper tends to solve the problem of sample truth acquisition for SAR classification by exploring a new sample labeling method and the corresponding learning method.
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It should be pointed out that there are many papers focusing on the stability problem of sampled-data systems, leakage delay, and sampled-data state feedback that have never been taken into consideration in the BAM neural networks.
Continuously recording turbidimeters provide a solution to the temporal problem of sampling.
How to build a synthetical sampling subset of data representing a larger one becomes a main problem of sampling experiments.
Moreover, the analysis of the general problem also leads to a solution to a problem of "sampling without replacement".
A brief reference is made to other studies which have addressed the problem of sampling contaminated sites.
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