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BMCBI
2006
146views more  BMCBI 2006»
14 years 9 months ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...
ASC
2004
14 years 9 months ago
Neural network-based colonoscopic diagnosis using on-line learning and differential evolution
In this paper, on-line training of neural networks is investigated in the context of computer-assisted colonoscopic diagnosis. A memory-based adaptation of the learning rate for t...
George D. Magoulas, Vassilis P. Plagianakos, Micha...
INTERSPEECH
2010
14 years 4 months ago
Investigation of full-sequence training of deep belief networks for speech recognition
Recently, Deep Belief Networks (DBNs) have been proposed for phone recognition and were found to achieve highly competitive performance. In the original DBNs, only framelevel info...
Abdel-rahman Mohamed, Dong Yu, L. Deng
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
98
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TNN
2010
185views Management» more  TNN 2010»
14 years 4 months ago
An adaptive multiobjective approach to evolving ART architectures
In this paper, we present the evolution of adaptive resonance theory (ART) neural network architectures (classifiers) using a multiobjective optimization approach. In particular, w...
Assem Kaylani, Michael Georgiopoulos, Mansooreh Mo...