Titlebook: Computers and Mathematics; Erich Kaltofen,Stephen M. Watt Conference proceedings 1989 Springer-Verlag New York Inc. 1989 Permutation.algeb

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蒙太奇

Health, Disease, and Productivitynerating set. Each call to this last test has worst case time .(..). A further reduction in time is achieved by using a fast algorithm for finding reduced generating sets. For groups with small bases, the running running time is .(..), which is optimal for the data structure used.

男生戴手銬

https://doi.org/10.1007/978-1-4020-4362-8ins no nuclei to assign its energy to the nearest nucleus. The lowest energy assigned to any nucleus is obviously a lower bound for the average energy per nucleus. Arguments given in [2] provide bounds for the energy contributed to a nucleus by all balls except those that are contained within a sphe

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https://doi.org/10.1007/978-1-4020-4362-8her conditions. In particular, we discovered that Kukles’ conditions for the existence of a center for a type of cubic differential systems are possibly incomplete, and presented a class of cubic differential systems with the origin as a 6-tuple focus from which one can create 6 limit cycles by a sm

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Computer Algebraic Methods for Investigating Plane Differential Systems of Center and Focus Typeher conditions. In particular, we discovered that Kukles’ conditions for the existence of a center for a type of cubic differential systems are possibly incomplete, and presented a class of cubic differential systems with the origin as a 6-tuple focus from which one can create 6 limit cycles by a sm

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https://doi.org/10.1007/978-1-4020-4362-8ch based on a computational “l(fā)earning” paradigm that incorporates a fundamental component of computer-aided obstruction identification with self-reduction to obtain known polynomial-time algorithms that do not depend on the knowledge of an entire obstruction set.

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Finite-Basis Theorems and a Computation-Integrated Approach to Obstruction Set Isolationch based on a computational “l(fā)earning” paradigm that incorporates a fundamental component of computer-aided obstruction identification with self-reduction to obtain known polynomial-time algorithms that do not depend on the knowledge of an entire obstruction set.

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Exact Algorithms for the Matrix-Triangularization Subresultant PRS Methodthod provides the smallest coefficients that can be expected without coefficient gcd computations. In this paper we present efficient, exact algorithms for the implementation of this new method, along with an example where bubble pivot is needed.