Results 291 to 300 of about 3,023,466 (332)
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Minimum Polarized Distance Codes
IBM Journal of Research and Development, 1961The choice of a code for a given application is influenced by many factors, such as economics, compatibility, and reliability. This paper is concerned solely with the reliability of codes, and shows how, for a given number of bits per character and a given minimum distance, the probability of undetected error in an asymmetric channel may be reduced by ...
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Journal of Mathematical Sciences, 2007
In the paper, we consider the estimation problem for an unknown density on independent observations. We use the minimum distance estimation method. It is shown that the accuracy of estimation is connected with the rate of increase of the entropy of the parametrical set. Bibliography: 9 titles.
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In the paper, we consider the estimation problem for an unknown density on independent observations. We use the minimum distance estimation method. It is shown that the accuracy of estimation is connected with the rate of increase of the entropy of the parametrical set. Bibliography: 9 titles.
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Minimum backward fréchet distance
Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2014We propose a new measure to capture similarity between polygonal curves, called the minimum backward Frechet distance. It is a natural optimization on the weak Frechet distance, a variant of the well-known Frechet distance. More specifically, for a given threshold e, we are searching for a pair of walks for two entities on the two input curves, T1 and ...
Amin Gheibi +3 more
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2002
The practice of obtaining estimators of parameters by minimizing a certain distance between some functions of observations and parameters has long been present in statistics. The classical examples of this method are the Least Square and the minimum Chi Square estimators.
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The practice of obtaining estimators of parameters by minimizing a certain distance between some functions of observations and parameters has long been present in statistics. The classical examples of this method are the Least Square and the minimum Chi Square estimators.
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1994
We introduce a new class of estimators — minimum distance estimators — and describe their properties in regular and nonstandard situations. These estimators, in the regular case of Hilbert metrics, are consistent and asymptotically normal. In nonstandard situations, their behavior is similar to the behavior of the MLE.
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We introduce a new class of estimators — minimum distance estimators — and describe their properties in regular and nonstandard situations. These estimators, in the regular case of Hilbert metrics, are consistent and asymptotically normal. In nonstandard situations, their behavior is similar to the behavior of the MLE.
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Generalized minimum distance decoding
IEEE Transactions on Information Theory, 1966We introduce a new distance measure which permits likelihood information to be used in algebraic minimum distance decoding techniques. We give an efficient decoding algorithm, and develop exponential bounds on the probability of not decoding correctly.
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Minimum Edge Distance Classifier
SPIE Proceedings, 1989This paper presents a direct template matching approach dependent on an object's edge boundary profile. The method for matching an unknown signature to the prestored templates involves a minimum edge distance criterion. The classifier design details are preceeded by a derivation of the mathematical link between boundary and silhouette moments for ...
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The rectilinear distance minisum problem with minimum distance constraints:
Location Science, 1995Summary: This paper describes a mathematical model for locating a single facility on a continuous plane, which considers transportation (or service) costs between the facility and a set of demand points as well as social costs arising from the undesirable characteristics of the facility.
Brimberg, J., Wesolowsky, G. O.
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Minimum‐distance methods based on quadratic distances for transforms
Canadian Journal of Statistics, 1987AbstractA class of minimum‐distance methods based on empirical transforms is considered. This class includes the minimum‐chi‐squared method, the K‐L method for empirical characteristic functions, and the analogous method for empirical moment generating functions.
Luong, A., Thompson, M. E.
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DISTANCE PRESERVING SUBTREES IN MINIMUM AVERAGE DISTANCE SPANNING TREES
Discrete Mathematics, Algorithms and Applications, 2013Given an undirected graph G = (V, E) with n vertices and a positive length w(e) on each edge e ∈ E, we consider Minimum Average Distance (MAD) spanning trees i.e., trees that minimize the path length summed over all pairs of vertices. One of the first results on this problem is due to Wong who showed in 1980 that a Distance Preserving (DP) spanning ...
Lyaudet, Laurent +3 more
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