Sentence examples for maximal matching method from inspiring English sources

Exact(6)

As the worst case complexity for the maximal matching method is, the computation complexity for CES can be stated as.

When the RN is placed at each shared region, the optimal relay assignment can be obtained by utilizing the maximal matching method.

In this section, we first present a maximal matching method to solve the RA-CORP problem if the RNs' positions are known.

As a preliminary step, we employ a maximal matching method to find the optimal relay node assignment for the static network scenario, that is, all RNs are fixed.

Based on Algorithm 2, the complexity of the GICO algorithm is, because the procedure from line 4 to line 5 is iterated times, and the worst case complexity for the maximal matching method is.

As an initial setup, we consider the subproblem of Relay Assignment for COverage-oriented Relay Placement (RA-CORP) which is, for any given RNs' placement, to obtain the optimal associations between RNs and MNs using maximal matching method.

Similar(54)

Node-link-based algorithm with Hungarian method of maximal matching has almost twice the broadcast reachable nodes and assigned link rate, compared to the basic algorithms.

The maximal matching algorithm for maximizing the assortativity index (hereafter, referred to as the maximal assortative matching algorithm, MAM) prefers to include edges that have lower assortativity weight as part of the matching.

The rest of the paper is organized as follows: Sect. 2 presents the maximal assortative matching (MAM) algorithm for an arbitrary graph and discusses its flexibility to be used as a maximal matching algorithm for maximizing the number of nodes matched (hereafter referred to as the maximal node matching algorithm, MNM).

First, we apply a shape matching method to coarsely register images to find out maximal overlap to exploit the spatial correlation between images acquired from neighboring sensors.

We define the problem of maximal assortativity matching (MAM) as a variant of the maximal matching problem wherein we want to maximize the similarity between the end vertices (with respect to any particular measure for node weight) constituting the matching.

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