A new algorithm is presented for finding a maximum independent set of a circular-arc graph. When the graph is given in the form of a family of n arcs, our algorithm requires only O(n⋅logn)<span style="display:...
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With a linear robotarm - driven by a DC motor, with a maximum velocity of 1 m/s, an acceleration of 5 m/s2, an accuracy of 0.01 mm and for loads up to 50 kg - a trajectory control is performed. The desired trajectory ...
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Given a point set in the plane and a fixed planar region (window) a window query consists of enumerating the points in a translate of the region. A recently presented result demonstrates that there is astatic data str...
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Given a point set in the plane and a fixed planar region (window) a window query consists of enumerating the points in a translate of the region. A recently presented result demonstrates that there is astatic data structure, of optimal size, that solves window queries for convex regions in optimal time. We give a data structure, of optimal size, that not only supports window queries in optimal time for, possibly nonconvex, polygonal windows, but also allows updating of the point set in optimal time.
作者：
COLE, RJDep. Comp. Sci.
Courant Inst. Math. Sci. New York Univ. 251 Mercer St. New York NY 10012 USA
The author gives an optimally efficient parallel algorithm for selection on the EREW PRAM. It requires a linear number of operations and O(log n log*n) time. A modification of the algorithm runs on the CRCW PRAM. It r...
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The author gives an optimally efficient parallel algorithm for selection on the EREW PRAM. It requires a linear number of operations and O(log n log*n) time. A modification of the algorithm runs on the CRCW PRAM. It requires a linear number of operations and O(log n log*n/log log n) time.
A parallel algorithm is described for merging two sorted vectors of total length N. The algorithm runs on a shared-memory model of parallel computation that disallows more than one processor to simultaneously read fro...
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A parallel algorithm is described for merging two sorted vectors of total length N. The algorithm runs on a shared-memory model of parallel computation that disallows more than one processor to simultaneously read from or write into the same memory location. It uses k processors where l ¿ k ¿ N and requires O(N/k + log k � log N) time. The proposed approach for merging leads to a parallel sorting algorithm that sorts a vector of length N in O(log2 k + N/k) log N) time. Because they modify their behavior and hence their running time according to the number of available processors, the two new algorithms are said to be self-reconfiguring. In addition, both algorithms are optimal, for k ¿ N/log2 N, in view of the ¿(N) and ¿(N log N) lower bounds on merging and sorting, respectively.
This paper presents some results obtained in time series forecasting using two nonstandard approaches and compares them with those obtained by usual statistical techniques. In particular, a new method based on recent ...
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This paper presents some results obtained in time series forecasting using two nonstandard approaches and compares them with those obtained by usual statistical techniques. In particular, a new method based on recent results of the General Theory of optimal algorithms is considered. This method may be useful when no reliable statistical hypotheses can be made or when a limited number of observations is available. Moreover, a nonlinear modelling technique based on Group Method of Data Handling (GMDH) is also considered to derive forecasts. The well-known Wolf Sunspot Numbers and Annual Canadian Lynx Trappings series are analyzed; the optimal Error Predictor is also applied to a recently published demographic series on Australian Births. The reported results show that the optimal Error and GMDH predictors provide accurate one step ahead forecasts with respect to those obtained by some linear and nonlinear statistical models. Furthermore, the optimal Error Predictor shows very good performances in multistep forecasting. [ABSTRACT FROM AUTHOR]
This correspondence studies the time complexity of the parallel computation of the product C = A.B of two dense square matrices A, B of order n, on a class of rectangular orthogonally connected systolic arrays, which ...
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This correspondence studies the time complexity of the parallel computation of the product C = A.B of two dense square matrices A, B of order n, on a class of rectangular orthogonally connected systolic arrays, which are the two-dimensional extensions of the classical pipeline scheme. Such arrays are composed of multiply-add cells without local memory, and, as C is computed, the coefficients cij move vertically, whereas aik and bkj move horizontally in opposite directions. We first introduce a combinatorial formulation of the problem. Then we show that, if the cycle-time of a multiply-add cell is taken as time unit, and if T(p, m) denotes the running time of an optimal algorithm associated with an array of size p x m, then Minpm T(p,m) = 3n -2, and the minimum value of p.m for which this bound is tight is n.n [resp. n(n + 1)] if n is odd (resp. even). When compared to the algorithms previously proposed for the class of arrays based on cells without local memory, the solutions exhibited here appear to be the best, because they are the only ones which run in time T < = 3n -2 on a network of size S < = n(n + 1).
Les auteurs se proposent d’étudier la complexité d’un algorithme de décodage pondéré des codes linéaires en blocs précédemment publié et de certaines de ses variantes sim...
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Les auteurs se proposent d’étudier la complexité d’un algorithme de décodage pondéré des codes linéaires en blocs précédemment publié et de certaines de ses variantes simplifiées, en se restreignant au cas binaire. On présente à cet effet des calculs basés sur un modèle simplifié du fonctionnement du décodeur ainsi que des résultats de sa simulation. On commence par rappeler la description de cet algorithme en se référant au diagramme du treillis associé au code. Une description probabiliste du fonctionnement de l’algorithme sert d’introduction à un modèle dans lequel les ?cotes? associées à chaque chemin du treillis, qu’il s’agit de comparer, sont scindées en deux termes additifs, l’un certain, l’autre aléatoire. Une évaluation de la complexité de l’algorithme optimal et de certaines de ses variantes simplifiées est développée à partir de ce modèle. La méthode de simulation de l’algorithme et de ses variantes, ainsi que les résultats obtenus, sont enfin présentés.
The Voronoi diagram of a finite set S of points in the Euclidean plane is a well-known geometric model useful for applications in various areas of science. A new and optimal algorithm is outlined for computing collin...
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The Voronoi diagram of a finite set S of points in the Euclidean plane is a well-known geometric model useful for applications in various areas of science. A new and optimal algorithm is outlined for computing collinear weighted Voronoi diagrams (WVD) that is conceptually simpler and appears very attractive for practical implementations. The approach is based on 2-dimensional interpretation of the diagram. This interpretation also permits the establishment of exact upper bounds on the number of components realized by the diagram. It is believed that, as for the planar diagram, the optimal algorithm for collinear WVDs is of merit to several areas of science outside computer science.
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