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IJON
2002
154views more  IJON 2002»
13 years 8 months ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec
NN
2002
Springer
105views Neural Networks» more  NN 2002»
13 years 8 months ago
The computational role of dopamine D1 receptors in working memory
The prefrontal cortex (PFC) is essential for working memory, which is the ability to transiently hold and manipulate information necessary for generating forthcoming action. PFC n...
Daniel Durstewitz, Jeremy K. Seamans
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 7 months ago
Variable resolution decomposition for robotic navigation under a POMDP framework
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
Robert Kaplow, Amin Atrash, Joelle Pineau
TPDS
2010
89views more  TPDS 2010»
13 years 7 months ago
Energy-Efficient Protocol for Deterministic and Probabilistic Coverage in Sensor Networks
—Various sensor types, e.g., temperature, humidity, and acoustic, sense physical phenomena in different ways, and thus, are expected to have different sensing models. Even for th...
Mohamed Hefeeda, Hossein Ahmadi
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
13 years 7 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer