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
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