DocumentCode
294916
Title
Multi-intersected/recursive textured algorithms for large-scale convex optimization problems
Author
Huang, Garng M. ; Hsieh, Shih-Chieh
Author_Institution
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Volume
2
fYear
1995
fDate
13-15 Dec 1995
Firstpage
1121
Abstract
In this paper, we extend our textured algorithm to multi-intersected textured models. We also describe the recursive textured decomposition process as a tree, in which we can obtain the overall solution by consolidating the end subsystem solutions. The proposed algorithms, their properties, and the theorems for exact convergence are then addressed. The worst-case time complexity of the algorithm with complete tree structure, in which parents in the same recursion level have the same number of children, is analyzed. Examples are given to demonstrate the use of the algorithms and the trade-off among the number of recursion levels, the number of sequential computing steps, and problem size reduction
Keywords
computational complexity; convergence of numerical methods; nonlinear programming; trees (mathematics); convergence; large-scale convex optimization; multi-intersected textured models; textured decomposition method; tree structure; worst-case time complexity; Algorithm design and analysis; Convergence; Decision feedback equalizers; Ear; Functional programming; Large-scale systems; Linear programming; Time division multiplexing; Tree data structures; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location
New Orleans, LA
ISSN
0191-2216
Print_ISBN
0-7803-2685-7
Type
conf
DOI
10.1109/CDC.1995.480241
Filename
480241
Link To Document