140 search results - page 8 / 28 » Perspectives and challenges for recurrent neural network tra... |
ISNN
2007
Springer
14 years 1 months ago
2007
Springer
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...
ICANN
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. We apply Long Short-Term Memory (LSTM) recurrent neural networks to a large corpus of unprompted speech- the German part of the VERBMOBIL corpus. Training first on a fra...
ESANN
2007
13 years 9 months ago
2007
Training recurrent neural networks is hard. Recently it has however been discovered that it is possible to just construct a random recurrent topology, and only train a single linea...
TNN
1998
13 years 7 months ago
1998
—Recurrent neural networks processing symbolic strings can be regarded as adaptive neural parsers. Given a set of positive and negative examples, picked up from a given language,...
IJON
1998
13 years 7 months ago
1998
Paper [1] aimed at providing a unified presentation of neural network architectures. We show in the present comment (i) that the canonical form of recurrent neural networks presen...