On maximal weight solutions of two matricial moment problems in the nondegenerate case

2016 ◽  
Vol 506 ◽  
pp. 413-444
Author(s):  
Xu-Zhou Zhan ◽  
Yong-Jian Hu ◽  
Gong-Ning Chen
Keyword(s):  
Moment Problems ◽  
Maximal Weight ◽  
Nondegenerate Case

scholarly journals A multi-level algorithm for the solution of moment problems

1998 ◽  
Vol 19 (3-4) ◽  
pp. 353-375 ◽  
Author(s):  
Otmar Scherzer ◽  
Thomas Strohmer
Keyword(s):  
Moment Problems ◽  
Multi Level

On the moment problems

1997 ◽  
Vol 35 (1) ◽  
pp. 85-90 ◽  
Author(s):  
Gwo Dong Lin
Keyword(s):  
Moment Problems ◽  
The Moment

scholarly journals On the analytic form of the discrete Kramer sampling theorem

2001 ◽  
Vol 25 (11) ◽  
pp. 709-715 ◽  
Author(s):  
Antonio G. García ◽  
Miguel A. Hernández-Medina ◽  
María J. Muñoz-Bouzo
Keyword(s):  
Orthogonal Polynomials ◽  
Boundary Value Problems ◽  
Boundary Value ◽  
Analytic Form ◽  
Sampling Theorem ◽  
Discrete Version ◽  
Moment Problems ◽  
Sturm Liouville ◽  
The Subject ◽  
Sampling Expansions

The classical Kramer sampling theorem is, in the subject of self-adjoint boundary value problems, one of the richest sources to obtain sampling expansions. It has become very fruitful in connection with discrete Sturm-Liouville problems. In this paper a discrete version of the analytic Kramer sampling theorem is proved. Orthogonal polynomials arising from indeterminate Hamburger moment problems as well as polynomials of the second kind associated with them provide examples of Kramer analytic kernels.

Matrix moment problems with constraints

PAMM ◽  
2002 ◽  
Vol 1 (1) ◽  
pp. 420 ◽  
Author(s):  
V.M. Adamyan ◽  
I.M. Tkachenko
Keyword(s):  
Moment Problems ◽  
Matrix Moment

Exit Times, Moment Problems and Comparison Theorems

2012 ◽  
Vol 38 (4) ◽  
pp. 1365-1372 ◽  
Author(s):  
Patrick McDonald
Keyword(s):  
Comparison Theorems ◽  
Moment Problems ◽  
Exit Times

Kruskal's theorem for matroids

1968 ◽  
Vol 64 (1) ◽  
pp. 3-4 ◽  
Author(s):  
D. J. A. Welsh
Keyword(s):  
Vector Space ◽  
Finite Subset ◽  
Spanning Tree ◽  
General Theorem ◽  
Independent Set ◽  
Easy Method ◽  
Maximal Weight ◽  
Linearly Independent ◽  
Kruskal’S Theorem ◽  
Special Case

AbstractKruskal's theorem for obtaining a minimal (maximal) spanning tree of a graph is shown to be a special case of a more general theorem for matroid spaces in which each element of the matroid has an associated weight. Since any finite subset of a vector space can be regarded as a matroid space this theorem gives an easy method of selecting a linearly independent set of vectors of minimal (maximal) weight.

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