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» Optimizing number of hidden neurons in neural networks
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NN
1998
Springer
13 years 6 months ago
Statistical estimation of the number of hidden units for feedforward neural networks
The number of required hidden units is statistically estimated for feedforward neural networks that are constructed by adding hidden units one by one. The output error decreases w...
Osamu Fujita
ESANN
2006
13 years 8 months ago
On the selection of hidden neurons with heuristic search strategies for approximation
Abstract. Feature Selection techniques usually follow some search strategy to select a suitable subset from a set of features. Most neural network growing algorithms perform a sear...
Ignacio Barrio, Enrique Romero, Lluís A. Be...
FUZZY
2004
Springer
125views Fuzzy Logic» more  FUZZY 2004»
14 years 12 days ago
A Feedforward Neural Network based on Multi-Valued Neurons
A feedforward neural network based on multi-valued neurons is considered in the paper. It is shown that using a traditional feedforward architecture and a high functionality multi-...
Igor N. Aizenberg, Claudio Moraga, Dmitriy Paliy
ISNN
2005
Springer
14 years 15 days ago
A Novel Solid Neuron-Network Chip Based on Both Biological and Artificial Neural Network Theories
Built on the theories of biological neural network, artificial neural network methods have shown many significant advantages. However, the memory space in an artificial neural chip...
Zihong Liu, Zhihua Wang, Guolin Li, Zhiping Yu
DMIN
2006
126views Data Mining» more  DMIN 2006»
13 years 8 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...