๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Complexity of Computing the Local Dimension of a Semialgebraic Set

โœ Scribed by Nicolai Vorobjov


Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
521 KB
Volume
27
Category
Article
ISSN
0747-7171

No coin nor oath required. For personal study only.

โœฆ Synopsis


The paper describes several algorithms related to a problem of computing the local dimension of a semialgebraic set. Let a semialgebraic set V be defined by a system of k inequalities of the form f โ‰ฅ 0 with f โˆˆ R[X 1 , . . . , Xn], deg(f ) < d, and x โˆˆ V . An algorithm is constructed for computing the dimension of the Zariski tangent space to V at x in time (kd) O(n) . Let x belong to a stratum of codimension lx in V with respect to a smooth stratification of V . Another algorithm computes the local dimension dimx(V ) with the complexity (k(lx + 1)d) O(l 2

x n) . If l = max xโˆˆV lx, and for every connected component the local dimension is the same at each point, then the algorithm computes the dimension of every connected component with complexity (k(l + 1)d) O(l 2 n) . If V is a real algebraic variety defined by a system of equations, then the complexity of the algorithm is less than kd O(l 2 n) , and the algorithm also finds the dimension of the tangent space to V at x in time kd O(n) . When l is fixed, like in the case of a smooth V , the complexity bounds for computing the local dimension are (kd) O(n) and kd O(n) respectively. A third algorithm finds the singular locus of V in time (kd) O(n 2 ) .


๐Ÿ“œ SIMILAR VOLUMES


The Computational Complexity of Choice S
โœ Felix Brandt; Felix Fischer; Paul Harrenstein ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 136 KB

## Abstract Social choice rules are often evaluated and compared by inquiring whether they satisfy certain desirable criteria such as the __Condorcet criterion__, which states that an alternative should always be chosen when more than half of the voters prefer it over any other alternative. Many of

Computing the correlation dimension on a
โœ Corana, Angelo ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 228 KB ๐Ÿ‘ 1 views

We present a parallel algorithm for computing the correlation dimension (D2) from a time series generated by a dynamic system, using the method of correlation integrals, which essentially requires the computation of distances among a set of points in the state space. The parallelization is suitable