Title :
Neurofuzzy interpolation. II. Reducing complexity of description
Author :
Regattieri, M. ; Zuben, F.J.V. ; Rocha, A.F.
Author_Institution :
Campinas Univ., SP, Brazil
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;
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
DOI :
10.1109/ICNN.1993.298836
