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TNN
2010
234views Management» more  TNN 2010»
13 years 4 hour ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
DMIN
2006
126views Data Mining» more  DMIN 2006»
13 years 6 months ago
Comparison and Analysis of Mutation-based Evolutionary Algorithms for ANN Parameters Optimization
Mutation-based Evolutionary Algorithms, also known as Evolutionary Programming (EP) are commonly applied to Artificial Neural Networks (ANN) parameters optimization. This paper pre...
Kristina Davoian, Alexander Reichel, Wolfram-Manfr...
IJCNN
2006
IEEE
13 years 11 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
IMCSIT
2010
13 years 3 months ago
Emotional Speech Analysis using Artificial Neural Networks
In the present text, we deal with the problem of classification of speech emotion. Problems of speech processing are addressed through the use of artificial neural networks (ANN). ...
Jana Tucková, Martin Sramka
ENGL
2008
98views more  ENGL 2008»
13 years 5 months ago
A New Wavelet Back Propagation Neural Networks for Structural Dynamic Analysis
dynamic analysis of structures for earthquake induced loads is very expensive in terms of the computational burden. In this study, to reduce the computational effort a new neural s...
R. Kamyab Moghadas, S. Gholizadeh