40 resultados para Semigroups of linear operators
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2000 Mathematics Subject Classification: Primary 47A48, 93B28, 47A65; Secondary 34C94.
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2000 Mathematics Subject Classification: Primary 47A20, 47A45; Secondary 47A48.
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Mathematics Subject Classification: 26A33, 47A60, 30C15.
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2000 Mathematics Subject Classification: 26A33, 33C60, 44A20
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2000 Mathematics Subject Classification: Primary 47B47, 47B10; Secondary 47A30.
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AMS Subject Classification 2010: 41A25, 41A27, 41A35, 41A36, 41A40, 42Al6, 42A85.
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In this paper, we prove the nonexistence of arcs with parameters (232, 48) and (233, 48) in PG(4,5). This rules out the existence of linear codes with parameters [232,5,184] and [233,5,185] over the field with five elements and improves two instances in the recent tables by Maruta, Shinohara and Kikui of optimal codes of dimension 5 over F5.
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The theorem of Czerniakiewicz and Makar-Limanov, that all the automorphisms of a free algebra of rank two are tame is proved here by showing that the group of these automorphisms is the free product of two groups (amalgamating their intersection), the group of all affine automorphisms and the group of all triangular automorphisms. The method consists in finding a bipolar structure. As a consequence every finite subgroup of automorphisms (in characteristic zero) is shown to be conjugate to a group of linear automorphisms.
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In this paper are examined some classes of linear and non-linear analytical systems of partial differential equations. Compatibility conditions are found and if they are satisfied, the solutions are given as functional series in a neighborhood of a given point (x = 0).
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The basic conceptions of the model „entity-relationship” as entities, relationships, structural constraints of the relationships (index cardinality, participation degree, and structural constraints of kind (min, max)) are considered and formalized in terms of relations theory. For the binary relations two operators (min and max) are introduced; structural constraints are determined in terms of the operators; the main theorem about compatibility of these operators’ values on the source relation and inversion to it is given here.
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In this article, we examine a realization of an open addressing hash table in the chained allocated memory, giving us the opportunity to decrease the number of linear probing when a given element has not been inserted in the table.
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Prognostic procedures can be based on ranked linear models. Ranked regression type models are designed on the basis of feature vectors combined with set of relations defined on selected pairs of these vectors. Feature vectors are composed of numerical results of measurements on particular objects or events. Ranked relations defined on selected pairs of feature vectors represent additional knowledge and can reflect experts' opinion about considered objects. Ranked models have the form of linear transformations of feature vectors on a line which preserve a given set of relations in the best manner possible. Ranked models can be designed through the minimization of a special type of convex and piecewise linear (CPL) criterion functions. Some sets of ranked relations cannot be well represented by one ranked model. Decomposition of global model into a family of local ranked models could improve representation. A procedures of ranked models decomposition is described in this paper.
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In this paper, a novel approach for character recognition has been presented with the help of genetic operators which have evolved from biological genetics and help us to achieve highly accurate results. A genetic algorithm approach has been described in which the biological haploid chromosomes have been implemented using a single row bit pattern of 315 values which have been operated upon by various genetic operators. A set of characters are taken as an initial population from which various new generations of characters are generated with the help of selection, crossover and mutation. Variations of population of characters are evolved from which the fittest solution is found by subjecting the various populations to a new fitness function developed. The methodology works and reduces the dissimilarity coefficient found by the fitness function between the character to be recognized and members of the populations and on reaching threshold limit of the error found from dissimilarity, it recognizes the character. As the new population is being generated from the older population, traits are passed on from one generation to another. We present a methodology with the help of which we are able to achieve highly efficient character recognition.
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Mathematics Subject Classification: 26A33, 31C25, 35S99, 47D07.
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2000 Mathematics Subject Classification: 26A33 (primary), 35S15 (secondary)