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AMC
2008
99views more  AMC 2008»
14 years 10 months ago
Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
Roderick V. N. Melnik
ICMCS
2005
IEEE
68views Multimedia» more  ICMCS 2005»
15 years 3 months ago
A neural-field-like approach for modeling human group actions in meetings
In this paper we investigate a new architecture for recognizing human group actions in meetings. These group actions provide a basis that enables effective browsing and querying i...
Stephan Reiter, Gerhard Rigoll
PPSN
2004
Springer
15 years 3 months ago
Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
JCP
2008
144views more  JCP 2008»
14 years 9 months ago
A Neural Network Controller for Trajectory Control of Industrial Robot Manipulators
This paper addresses the issue of trajectory tracking control based on a neural network controller for industrial manipulators. A new control scheme is proposed based on neural net...
Zhao-Hui Jiang, Taiki Ishida
EPS
1995
Springer
15 years 1 months ago
PANIC: A Parallel Evolutionary Rule Based System
PANIC (Parallelism And Neural networks In Classifier systems) is a parallel system to evolve behavioral strategies codified by sets of rules. It integrates several adaptive techni...
Antonella Giani, Fabrizio Baiardi, Antonina Starit...