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» Neural Networks and Complexity Theory
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IJON
2007
184views more  IJON 2007»
14 years 9 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
IJCNN
2000
IEEE
15 years 2 months ago
Input Window Size and Neural Network Predictors
Neural Network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results fro...
Ray J. Frank, Neil Davey, S. P. Hunt
KAIS
2000
106views more  KAIS 2000»
14 years 9 months ago
FANNC: A Fast Adaptive Neural Network Classifier
In this paper, a fast adaptive neural network classifier named FANNC is proposed. FANNC exploits the advantages of both adaptive resonance theory and field theory. It needs only on...
Zhi-Hua Zhou, Shifu Chen, Zhaoqian Chen
72
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IJON
2006
111views more  IJON 2006»
14 years 9 months ago
Dynamic pruning algorithm for multilayer perceptron based neural control systems
Generalization ability of neural networks is very important and a rule of thumb for good generalization in neural systems is that the smallest system should be used to fit the tra...
Jie Ni, Qing Song
NIPS
2000
14 years 11 months ago
Foundations for a Circuit Complexity Theory of Sensory Processing
We introduce total wire length as salient complexity measure for an analysis of the circuit complexity of sensory processing in biological neural systems and neuromorphic engineer...
Robert A. Legenstein, Wolfgang Maass