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» The Recurrent Control Neural Network
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CEC
2009
IEEE
14 years 4 months ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
TFS
2008
129views more  TFS 2008»
13 years 8 months ago
A Functional-Link-Based Neurofuzzy Network for Nonlinear System Control
Abstract--This study presents a functional-link-based neurofuzzy network (FLNFN) structure for nonlinear system control. The proposed FLNFN model uses a functional link neural netw...
Cheng-Hung Chen, Cheng-Jian Lin, Chin-Teng Lin
CCECE
2006
IEEE
14 years 3 months ago
Adaptive Bilateral Control using Operator Elbow Impedance
— Human arm dynamics can be used for control of human-machine interfaces in haptic applications. In this paper, a novel method for online estimation of human operator elbow imped...
Farid Mobasser, Keyvan Hashtrudi-Zaad
GECCO
2009
Springer
14 years 2 months ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz
IROS
2009
IEEE
164views Robotics» more  IROS 2009»
14 years 4 months ago
Complex networks of simple neurons for bipedal locomotion
— Fluid bipedal locomotion remains a significant challenge for humanoid robotics. Recent bio-inspired approaches have made significant progress by using small numbers of tightl...
Brian F. Allen, Petros Faloutsos