In the experience of the authors, the application of ARD is limited by the size of the datasets, being not applicable in practice to datasets with more than several thousands of datapoints, or with more than several hundreds of descriptors.
However, because of the high computation efforts they are not applicable in practice.
50% to 70% of the measurement configurations lead to collisions so that the designs are not applicable in practice.
This idea, however, is not applicable in practice since the exact value of the gross error ε is not known.
As complex topologies are not applicable in practice due to the problem of state explosion, modelling the system behaviour as unsophisticated as possible is very important [15].
Since the above presented formulation is not applicable in practice, a reformulation by a Dantzig-Wolfe reformulation is a promising alternative.
However, it is not applicable in practice for the reason that the estimation of clutter eigenvectors requires training data to make eigen decomposition and is computationally complex.
Thus, an MNB turbo-decoder equipped with a mechanism to stop the iterations based on the minAPP criterion (easily implementable in practice) performs on average 1.5 more iterations than the one based on the genie criterion (not applicable in practice).
