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TON
2008
139views more  TON 2008»
13 years 7 months ago
Stochastic learning solution for distributed discrete power control game in wireless data networks
Distributed power control is an important issue in wireless networks. Recently, noncooperative game theory has been applied to investigate interesting solutions to this problem. Th...
Yiping Xing, Rajarathnam Chandramouli
CN
2007
149views more  CN 2007»
13 years 7 months ago
Adaptive congestion protocol: A congestion control protocol with learning capability
There is strong evidence that the current implementation of TCP will perform poorly in future high speed networks. To address this problem many congestion control protocols have b...
Marios Lestas, Andreas Pitsillides, Petros A. Ioan...
ISNN
2007
Springer
14 years 1 months ago
Recurrent Fuzzy CMAC for Nonlinear System Modeling
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...
Floriberto Ortiz Rodriguez, Wen Yu, Marco A. Moren...
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
14 years 1 months ago
Post-processing clustering to reduce XCS variability
XCS is a stochastic algorithm, so it does not guarantee to produce the same results when run with the same input. When interpretability matters, obtaining a single, stable result ...
Flavio Baronti, Alessandro Passaro, Antonina Stari...
IJAR
2008
119views more  IJAR 2008»
13 years 7 months ago
Adapting Bayes network structures to non-stationary domains
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
Søren Holbech Nielsen, Thomas D. Nielsen