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ACRI
2004
Springer
15 years 2 months ago
Neuropercolation: A Random Cellular Automata Approach to Spatio-temporal Neurodynamics
Abstract. We outline the basic principles of neuropercolation, a generalized percolation model motivated by the dynamical properties of the neuropil, the densely interconnected neu...
Robert Kozma, Marko Puljic, Paul Balister, B&eacut...
NN
2006
Springer
108views Neural Networks» more  NN 2006»
14 years 9 months ago
Performance analysis of LVQ algorithms: A statistical physics approach
Learning vector quantization (LVQ) constitutes a powerful and intuitive method for adaptive nearest prototype classification. However, original LVQ has been introduced based on he...
Anarta Ghosh, Michael Biehl, Barbara Hammer
BC
2000
77views more  BC 2000»
14 years 9 months ago
Generic origins of irregular spiking in neocortical networks
We identify generic sources of complex and irregular spiking in biological neural networks. For the network description, we operate on a mathematically exact mesoscopic approach. S...
Ruedi Stoop, L. A. Bunimovich, Willi-Hans Steeb
86
Voted
TNN
1998
146views more  TNN 1998»
14 years 9 months ago
Fuzzy lattice neural network (FLNN): a hybrid model for learning
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
Vassilios Petridis, Vassilis G. Kaburlasos
IJCNN
2006
IEEE
15 years 3 months ago
Improvement of an Artificial Neural Network Model using Min-Max Preprocessing for the Prediction of Wave-induced Seabed Liquefac
—In the past decade, artificial neural networks (ANNs) have been widely applied to the engineering problems with a complicated system. ANNs are becoming an important alternative ...
Deaho Cha, Michael Blumenstein, Hong Zhang, Dong-S...