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IJCNN
2006
IEEE
15 years 3 months ago
A Very Small Chaotic Neural Net
— Previously we have shown that chaos can arise in networks of physically realistic neurons [1], [2]. Those networks contain a moderate to large number of units connected in a sp...
Carlos Lourenco
72
Voted
ICA
2010
Springer
14 years 8 months ago
Time Series Causality Inference Using Echo State Networks
One potential strength of recurrent neural networks (RNNs) is their – theoretical – ability to find a connection between cause and consequence in time series in an constraint-...
Norbert Michael Mayer, Oliver Obst, Chang Yu-Chen
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
81
Voted
IJCNN
2000
IEEE
15 years 2 months ago
Support Vector Machine for Regression and Applications to Financial Forecasting
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...
Theodore B. Trafalis, Huseyin Ince
IJON
2008
118views more  IJON 2008»
14 years 9 months ago
Incremental extreme learning machine with fully complex hidden nodes
Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden nodes, IEEE Trans. Neural Networks 17(4) (2006) 879
Guang-Bin Huang, Ming-Bin Li, Lei Chen, Chee Kheon...