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77
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GECCO
2004
Springer
103views Optimization» more  GECCO 2004»
15 years 2 months ago
Training Neural Networks with GA Hybrid Algorithms
Abstract. Training neural networks is a complex task of great importance in the supervised learning field of research. In this work we tackle this problem with five algorithms, a...
Enrique Alba, J. Francisco Chicano
IAJIT
2010
117views more  IAJIT 2010»
14 years 8 months ago
Development of Neural Networks for Noise Reduction
: This paper describes the development of neural network models for noise reduction. The networks used to enhance the performance of modeling captured signals by reducing the effec...
Lubna Badri
SOFTCO
2004
Springer
15 years 2 months ago
Designing Neural Networks Using Gene Expression Programming
Abstract. An artificial neural network with all its elements is a rather complex structure, not easily constructed and/or trained to perform a particular task. Consequently, severa...
Cândida Ferreira
82
Voted
WCE
2007
14 years 10 months ago
Speech Recognition Model for Tamil Stops
—In this paper, a novel approach for implementing Tamil isolated speech phoneme recognition is described. While most of the literature on Automatic Speech Recognition (ASR) is ba...
Arumugam Rathinavelu, Anupriya Rajkumar, A. S. Mut...
NCA
2006
IEEE
14 years 9 months ago
Evolutionary training of hardware realizable multilayer perceptrons
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...
Vassilis P. Plagianakos, George D. Magoulas, Micha...