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Spaceefficient planar convex hull algorithms
 Proc. Latin American Theoretical Informatics
, 2002
"... A spaceefficient algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. We describe four spaceefficient algorithms for computing the convex hull of a planar point set. ..."
Abstract

Cited by 20 (1 self)
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A spaceefficient algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. We describe four spaceefficient algorithms for computing the convex hull of a planar point set.
Optimal inplace planar convex hull algorithms
 Proceedings of Latin American Theoretical Informatics (LATIN 2002), volume 2286 of Lecture Notes in Computer Science
, 2002
"... An inplace algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. In this paper we describe three inplace algorithms for computing the convex hull of a planar point set. All three algorithms are optima ..."
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Cited by 5 (2 self)
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An inplace algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. In this paper we describe three inplace algorithms for computing the convex hull of a planar point set. All three algorithms are optimal, some more so than others...
Online Piecewise Linear Approximation of Numerical Streams with Precision Guarantees*
"... Continuous “alwayson ” monitoring is beneficial for a number of applications, but potentially imposes a high load in terms of communication, storage and power consumption when a large number of variables need to be monitored. We introduce two new filtering techniques, swing filters and slide filter ..."
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Cited by 4 (0 self)
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Continuous “alwayson ” monitoring is beneficial for a number of applications, but potentially imposes a high load in terms of communication, storage and power consumption when a large number of variables need to be monitored. We introduce two new filtering techniques, swing filters and slide filters, that represent within a prescribed precision a timevarying numerical signal by a piecewise linear function, consisting of connected line segments for swing filters and (mostly) disconnected line segments for slide filters. We demonstrate the effectiveness of swing and slide filters in terms of their compression power by applying them to a reallife data set plus a variety of synthetic data sets. For nearly all combinations of signal behavior and precision requirements, the proposed techniques outperform the earlier approaches for online filtering in terms of data reduction. The slide filter, in particular, consistently dominates all other filters, with up to twofold improvement over the best of the previous techniques. 1.