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NPL
2000
112views more  NPL 2000»
13 years 4 months ago
Evolving Multilayer Perceptrons
Thispaper proposes anew version ofa method (G-Prop, geneticbackpropagation) that attempts to solve the problem of
Pedro A. Castillo Valdivieso, J. Carpio, Juan J. M...
IJON
2000
105views more  IJON 2000»
13 years 4 months ago
G-Prop: Global optimization of multilayer perceptrons using GAs
A general problem in model selection is to obtain the right parameters that make a model "t observed data. For a multilayer perceptron (MLP) trained with back-propagation (BP...
Pedro A. Castillo Valdivieso, Juan J. Merelo Guerv...
TNN
2008
96views more  TNN 2008»
13 years 4 months ago
Global Convergence and Limit Cycle Behavior of Weights of Perceptron
In this paper, it is found that the weights of a perceptron are bounded for all initial weights if there exists a nonempty set of initial weights that the weights of the perceptron...
Charlotte Yuk-Fan Ho, Bingo Wing-Kuen Ling, Hak-Ke...
EUROGP
2004
Springer
170views Optimization» more  EUROGP 2004»
13 years 8 months ago
Comparing Hybrid Systems to Design and Optimize Artificial Neural Networks
Abstract. In this paper we conduct a comparative study between hybrid methods to optimize multilayer perceptrons: a model that optimizes the architecture and initial weights of mul...
Pedro A. Castillo Valdivieso, Maribel Garcí...