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IJON
2007
98views more  IJON 2007»
15 years 6 months ago
Convergent design of piecewise linear neural networks
Piecewise linear networks (PLNs) are attractive because they can be trained quickly and provide good performance in many nonlinear approximation problems. Most existing design alg...
Hema Chandrasekaran, Jiang Li, W. H. Delashmit, Pr...
ESANN
2008
15 years 8 months ago
Petri nets design based on neural networks
Petri net faulty models are useful for reliability analysis and fault diagnosis of discrete event systems. Such models are difficult to work out as long as they must be computed ac...
Edouard Leclercq, Souleiman Ould el Medhi, Dimitri...
ESANN
2004
15 years 8 months ago
Input arrival-time-dependent decoding scheme for a spiking neural network
Spiking neurons model a type of biological neural system where information is encoded with spike times. In this paper, a new method for decoding input spikes according to their abs...
Hesham H. Amin, Robert H. Fujii
ECAI
2004
Springer
16 years 1 days ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
GECCO
2003
Springer
268views Optimization» more  GECCO 2003»
15 years 12 months ago
A Generalized Feedforward Neural Network Architecture and Its Training Using Two Stochastic Search Methods
Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks in which the synaptic interactions are mediated via a nonlinear mechanism called shuntin...
Abdesselam Bouzerdoum, Rainer Mueller