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NN
2000
Springer
192views Neural Networks» more  NN 2000»
15 years 6 months ago
A new algorithm for learning in piecewise-linear neural networks
Piecewise-linear (PWL) neural networks are widely known for their amenability to digital implementation. This paper presents a new algorithm for learning in PWL networks consistin...
Emad Gad, Amir F. Atiya, Samir I. Shaheen, Ayman E...
NN
1998
Springer
15 years 6 months ago
Distributed ARTMAP: a neural network for fast distributed supervised learning
Distributed coding at the hidden layer of a multi-layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically req...
Gail A. Carpenter, Boriana L. Milenova, Benjamin W...
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