The first approach can still be computed in O(1) while the second one depends on the approximation algorithm used and on the desired degree of accuracy.
Since BVSA uses a MCMC method to approximate the posterior distribution of the network structure its accuracy depends on the approximation error.
The positioning accuracy, attainable by a conventional network inversion scheme, depends on the approximation error present in the forward model.
The very small difference (16.53 against 16.9%%) depends on the approximation in the displacement step value used in the incremental analysis.
However, the accuracy of such analyzing methods largely depends on the approximations made.
Finally, we develop asymptotic approximation algorithms for both problems with ratios depending on the best known approximation ratio for the minimum Steiner tree problem.
Finally, it is worthwhile to note that from the implementation point of view on a general PQ instrument, the proposed analytical approach requires only some manipulations, of different complexities depending on the level of approximation desired (see (20), (21) and (22)), of the spectra which are already evaluated by the PQ instrument for the harmonic and interharmonic analysis.
It was shown to perform very well in practice, depending on the error in the approximation of the clutter parameters.
Since, due to the Galerkin method, the approximation of f is not defined on the boundary of the cells, we must introduce a numerical flux, that furnishes reasonable values of f on every (partial C_{alpha}), depending on the values of the approximation of f in the nearest neighborhoods of the cell (C_{alpha}) and on the sign of (mathbf{E} cdot mathbf{n}).
Depending on the methods and approximations used for breaking the ties, JFRP might require even more iterations.
