The Experts below are selected from a list of 560802 Experts worldwide ranked by ideXlab platform
Joao Borges Sousa - One of the best experts on this subject based on the ideXlab platform.
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Unmanned Aerial Vehicle Path Following: A Survey and Analysis of Algorithms for Fixed-Wing Unmanned Aerial Vehicless
IEEE Control Systems Magazine, 2014Co-Authors: P.b. Sujit, Srikanth Saripalli, Joao Borges SousaAbstract:Unmanned aerial vehicles (UAVs) are mainly used by military and government organizations, but with low-cost sensors, electronics, and airframes there is significant interest in using low-cost UAVs among aircraft hobbyists, academic researchers, and industries. Applications such as mapping, search and rescue, patrol, and surveillance require the UAV to autonomously follow a predefined path at a prescribed height. The most commonly used paths are straight lines and circular orbits. Path-following Algorithms ensure that the UAV will follow a predefined path in three or two dimensions at constant height. A basic requirement for these path-following Algorithms is that they must be accurate and robust to wind disturbances.
Rudolf Fleischer - One of the best experts on this subject based on the ideXlab platform.
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asymptotic complexity from experiments a case study for randomized Algorithms
Lecture Notes in Computer Science, 2000Co-Authors: Peter Sanders, Rudolf FleischerAbstract:In the Analysis of Algorithms we are usually interested in obtaining closed form expressions for their complexity, or at least asymptotic expressions in O(ċ)-notation. Unfortunately, there are fundamental reasons why we cannot obtain such expressions from experiments. This paper explains how we can at least come close to this goal using the scientific method. Besides the traditional role of experiments as a source of preliminary ideas for theoretical Analysis, experiments can test falsifiable hypotheses obtained by incomplete theoretical Analysis. Asymptotic behavior can also be deduced from stronger hypotheses which have been induced from experiments. As long as a complete mathematical Analysis is impossible, well tested hypotheses may have to take their place. Several examples for probabilistic problems are given where the average complexity can be well approximated experimentally so that the support for the hypotheses is quite strong. Randomized Shellsort has performance close to O(n log n); random polling dynamic load balancing between P processors achieves full load sharing in log2 P + O(log log P) steps; randomized writing to D independent disks using a shared buffer size W achieves average efficiency at least 1 - D/(2W).
Shanghua Teng - One of the best experts on this subject based on the ideXlab platform.
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smoothed Analysis of Algorithms why the simplex algorithm usually takes polynomial time
Journal of the ACM, 2004Co-Authors: Daniel A Spielman, Shanghua TengAbstract:We introduce the smoothed Analysis of Algorithms, which continuously interpolates between the worst-case and average-case analyses of Algorithms. In smoothed Analysis, we measure the maximum over inputs of the expected performance of an algorithm under small random perturbations of that input. We measure this performance in terms of both the input size and the magnitude of the perturbations. We show that the simplex algorithm has smoothed complexity polynomial in the input size and the standard deviation of Gaussian perturbations.
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smoothed Analysis of Algorithms why the simplex algorithm usually takes polynomial time
arXiv: Data Structures and Algorithms, 2001Co-Authors: Daniel A Spielman, Shanghua TengAbstract:We introduce the smoothed Analysis of Algorithms, which is a hybrid of the worst-case and average-case Analysis of Algorithms. In smoothed Analysis, we measure the maximum over inputs of the expected performance of an algorithm under small random perturbations of that input. We measure this performance in terms of both the input size and the magnitude of the perturbations. We show that the simplex algorithm has polynomial smoothed complexity.
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smoothed Analysis of Algorithms why the simplex algorithm usually takes polynomial time
Symposium on the Theory of Computing, 2001Co-Authors: Daniel A Spielman, Shanghua TengAbstract:We introduce the smoothed Analysis of Algorithms , which is a hybrid of the worst-case and average-case Analysis of Algorithms. Essentially, we study the performance of Algorithms under small random perturbations of their inputs. We show that the shadow-vertex simplex algorithm has polynomial smoothed complexity .
P.b. Sujit - One of the best experts on this subject based on the ideXlab platform.
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Unmanned Aerial Vehicle Path Following: A Survey and Analysis of Algorithms for Fixed-Wing Unmanned Aerial Vehicless
IEEE Control Systems Magazine, 2014Co-Authors: P.b. Sujit, Srikanth Saripalli, Joao Borges SousaAbstract:Unmanned aerial vehicles (UAVs) are mainly used by military and government organizations, but with low-cost sensors, electronics, and airframes there is significant interest in using low-cost UAVs among aircraft hobbyists, academic researchers, and industries. Applications such as mapping, search and rescue, patrol, and surveillance require the UAV to autonomously follow a predefined path at a prescribed height. The most commonly used paths are straight lines and circular orbits. Path-following Algorithms ensure that the UAV will follow a predefined path in three or two dimensions at constant height. A basic requirement for these path-following Algorithms is that they must be accurate and robust to wind disturbances.
Madhav V Marathe - One of the best experts on this subject based on the ideXlab platform.
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classical and contemporary shortest path problems in road networks implementation and experimental Analysis of the transims router
Lecture Notes in Computer Science, 2002Co-Authors: Christopher L Barrett, Keith R Bisset, Riko Jacob, Goran Konjevod, Madhav V MaratheAbstract:We describe and analyze empirically an implementation of some generalizations of Dijkstra's algorithm for shortest paths in graphs. The implementation formed a part of the TRANSIMS project at the Los Alamos National Laboratory. Besides offering the first implementation of the shortest path algorithm with regular language constraints, our code also solves problems with time-dependent edge delays in a quite general first-in-first-out model. We describe some details of our implementation and then analyze the behavior of the algorithm on real but extremely large transportation networks. Even though the questions we consider in our experiments are fundamental and natural, it appears that they have not been carefully examined before. A methodological contribution of the present work is the use of formal statistical methods to analyze the behaviour of our Algorithms. Although the statistical methods employed are simple, they provide a possibly novel approach to the experimental Analysis of Algorithms. Our results provide evidence for our claims of efficiency of the Algorithms described in a very practical setting.