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» Verifying Properties of Neural Networks
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EAAI
2006
157views more  EAAI 2006»
13 years 7 months ago
Blind source separation based on self-organizing neural network
This contribution describes a neural network that self-organizes to recover the underlying original sources from typical sensor signals. No particular information is required abou...
Anke Meyer-Bäse, Peter Gruber, Fabian J. Thei...
IROS
2009
IEEE
201views Robotics» more  IROS 2009»
14 years 2 months ago
Modeling tool-body assimilation using second-order Recurrent Neural Network
— Tool-body assimilation is one of the intelligent human abilities. Through trial and experience, humans are capable of using tools as if they are part of their own bodies. This ...
Shun Nishide, Tatsuhiro Nakagawa, Tetsuya Ogata, J...
IJCAI
1989
13 years 8 months ago
Training Feedforward Neural Networks Using Genetic Algorithms
Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
David J. Montana, Lawrence Davis
ACL
1998
13 years 9 months ago
Neural Network Recognition of Spelling Errors
One area in which artificial neural networks (ANNs) may strengthen NLP systems is in the identification of words under noisy conditions. In order to achieve this benefit when spel...
Mark Lewellen
TNN
2008
138views more  TNN 2008»
13 years 7 months ago
A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Zhenzhen Liu, Itamar Elhanany