• 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