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» Nonlinear predictive control based on neural multi-models
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ICANNGA
2007
Springer
153views Algorithms» more  ICANNGA 2007»
14 years 11 months ago
A Neural Framework for Robot Motor Learning Based on Memory Consolidation
Neural networks are a popular technique for learning the adaptive control of non-linear plants. When applied to the complex control of android robots, however, they suffer from se...
Heni Ben Amor, Shuhei Ikemoto, Takashi Minato, Ber...
IWANN
2005
Springer
15 years 3 months ago
Direct and Recursive Prediction of Time Series Using Mutual Information Selection
Abstract. This paper presents a comparison between direct and recursive prediction strategies. In order to perform the input selection, an approach based on mutual information is u...
Yongnan Ji, Jin Hao, Nima Reyhani, Amaury Lendasse
IJCNN
2006
IEEE
15 years 4 months ago
Using Neural Network to Enhance Assimilating Sea Surface Height Data into an Ocean Model
—A generic approach that allows extracting functional nonlinear dependencies and mappings between atmospheric or ocean state variables in a relatively simple form is presented. T...
Vladimir M. Krasnopolsky, Carlos J. Lozano, Deanna...
EAAI
2008
136views more  EAAI 2008»
14 years 10 months ago
Adaptive fuzzy control of a non-linear servo-drive: Theory and experimental results
Adaptive fuzzy control has been an active research area over the last decade and several stable adaptive fuzzy controllers have been proposed in the literature. Such controllers a...
Domenico Bellomo, David Naso, Robert Babuska
IJCNN
2008
IEEE
15 years 4 months ago
Learning associations of conjuncted fuzzy sets for data prediction
— Fuzzy Associative Conjuncted Maps (FASCOM) is a fuzzy neural network that represents information by conjuncting fuzzy sets and associates them through a combination of unsuperv...
Hanlin Goh, Joo-Hwee Lim, Chai Quek