Obtaining Initial Estimates of the Value Assignment and Calibration Curve Slope for the Stochastic
Approximation AlgorithmWe have designed the polygon
approximation algorithm and have analyzed the relation between the error and the number of polygon's edges.
In order to fulfil both the fault tolerance and energy efficiency requirements, we propose an efficient
approximation algorithm, Energy Efficient Maximum Disjoint Coverage (EMDC), with provable approximation bound.
By using an
approximation algorithm named Extended Hungarian is to minimize the number of steiner points on all the edges by means of extended cost in which the steiner points are calculated based on information about the nodes and the number of repeated values can be reduced.
As discussed in the introduction, the best
approximation algorithm for the densest k-subgraph problem currently known has an approximation ratio of O([n.sup.1/4+[delta]]) for any fixed [delta] > 0 [4] and it is conjectured that the inapproximability of the problem is of a similar magnitude.
Then the flop count [F.sub.l] for the low-rank
approximation Algorithm 2 is
In [19], an 0(n log n) time 12-factor
approximation algorithm is proposed for the problem of covering a set of line segments with minimum number of sensors.
In the last few years, there has been renewed interest in tackling this problem, this time from the perspective of
approximation algorithms.(2) In this paper, we carry this further by developing an
approximation algorithm based on the primal-dual schema.
IS is approximate equivalent to SP, in the sense that every
approximation algorithm solving the former also solves the latter within the same approximation ratio; this equivalence becomes very clear and intuitive by means of a graph (see Definition 3 at the beginning of Part II) defined for every SP-instance; proofs of this equivalence are found in Berge [1973] and Simon [1990].