• DocumentCode
    3088886
  • Title

    Lattice computing in hybrid intelligent systems

  • Author

    Grana, Manuel

  • Author_Institution
    Dept. CCIA, UPV, San Sebastian, Spain
  • fYear
    2012
  • fDate
    4-7 Dec. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Lattice Computing is the class of algorithms built on the basis of Lattice Theory. They either perform operations in the ring of the real valued spaces endowed with some (inf, sup) lattice operators, or use lattice theory to produce generalizations or fusions of conventional approaches. Lattice Computing has produced a variety of algorithms for data processing, classification, signal filtering over the last decades. On the other hand, hybrid algorithms are flourishing in the last years giving innovative solutions to new and old problems. Hybrid algorithms are free combinations of Computational Intelligence approaches for data mining, signal processing or general artificial intelligence questions, including statistical, nature and bio-inspired algorithms. In this paper we review some Lattice Computing approaches and how they have been hybridized for specific problems.
  • Keywords
    artificial intelligence; lattice theory; computational intelligence approaches; data mining; data processing; general artificial intelligence questions; hybrid algorithms; hybrid intelligent systems; lattice computing; lattice operators; lattice theory; signal filtering; signal processing; Associative memory; Conferences; Feature extraction; Fuzzy systems; Lattices; Neural networks; Signal processing algorithms; Hybrid Intelligent Systems; Lattice Computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hybrid Intelligent Systems (HIS), 2012 12th International Conference on
  • Conference_Location
    Pune
  • Print_ISBN
    978-1-4673-5114-0
  • Type

    conf

  • DOI
    10.1109/HIS.2012.6421300
  • Filename
    6421300