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» The Recurrent Control Neural Network
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155
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CEC
2009
IEEE
15 years 10 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
141
Voted
TFS
2008
129views more  TFS 2008»
15 years 1 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
135
Voted
CCECE
2006
IEEE
15 years 9 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
115
Voted
GECCO
2009
Springer
15 years 8 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»
15 years 10 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