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The mining algorithm generates a set of path patterns for each of these databases.
First, a set of path gains {hm,j; l = 0,…,L − 1} is generated to obtain the channel gains {Hm,j(n);n = 0,…,N c − 1}.
A set of path gains {h l ; l = 0 ~ L - 1} is generated using (3) to obtain channel gains {H(n); n = 0 ~ N c - 1}.
A set of path gains is generated using (1) to obtain the channel gain matrix for, and, then, the equalization matrix is computed using (6) for each source terminal.
Then, similarly to the work of Reeds and Shepp, we introduce a set of path types that contains the type of any subpath of a shortest path such that all contacts with obstacles are avoided, except possibly at the endpoints of the subpath.
Output: A Set of Path Strings, PSi, Steps (1) Set = All Path Strings of Page 1 - Schema PSs. (2) for i = 2 to N (3) do Temp = All PSs of Page i - Schema PSs (4) Set = intersection(Set, Temp) (5) Return Set. .
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Taking the RSS-based ranging technique introduced in the previous section and in order to obtain the actual path-loss exponents of the expression (5), the compatibility of distances does not have to be maximized in a global fashion, but for a set of path-loss exponents belonging to a feasible set of solutions.
Each origin-destination (O-D) pair w is connected by a set of paths (routes) represented by (K_{w}).
In both problems the cost is associated with a set of paths from a given vertex r to all the leaves of the constructed tree.
Given a lossy network, the objective function yields a set of paths that has the minimum number of channel uses in the case of equal link loss probabilities. .
In [24], the authors investigate the problem of finding the link scheduling for a set of paths in a WMN relying on the distance based-interference model.
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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