DocumentCode
1909438
Title
Neurofuzzy interpolation. II. Reducing complexity of description
Author
Regattieri, M. ; Zuben, F.J.V. ; Rocha, A.F.
Author_Institution
Campinas Univ., SP, Brazil
fYear
1993
fDate
1993
Firstpage
1835
Abstract
A neuro-fuzzy method of information compression is described. A neural-like structure is developed to operate on a set of sequential data in order to extract the minimal amount of data that can still accurately represent the entire original set. Fuzzy interpolation is used to regenerate the whole original set of data whenever necessary
Keywords
computational complexity; data compression; fuzzy set theory; interpolation; neural nets; complexity; fuzzy set theory; information compression; neural nets; neurofuzzy interpolation; sequential data; Actuators; Artificial intelligence; Data compression; Data mining; Humans; Information processing; Interpolation; Memory; Neurons; Power system restoration;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298836
Filename
298836
Link To Document