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» Multi-dimensional Recurrent Neural Networks
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ESANN
2003
13 years 11 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre
AIA
2006
13 years 11 months ago
A Recurrent Neural Filter for Adaptive Noise Cancellation
This paper presents a dynamic neural filter for adaptive noise cancellation. The cancellation task is transformed to a system-identification problem, which is tackled by use of th...
Paris A. Mastorocostas, Dimitris N. Varsamis, Cons...
ESANN
2007
13 years 11 months ago
An overview of reservoir computing: theory, applications and implementations
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...
Benjamin Schrauwen, David Verstraeten, Jan M. Van ...
TNN
1998
92views more  TNN 1998»
13 years 9 months ago
Inductive inference from noisy examples using the hybrid finite state filter
—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,...
Marco Gori, Marco Maggini, Enrico Martinelli, Giov...
ENGL
2006
135views more  ENGL 2006»
13 years 10 months ago
An Integral Plus States Adaptive Neural Control of Aerobic Continuous Stirred Tank Reactor
A direct adaptive neural network control system with and without integral action term is designed for the general class of continuous biological fermentation processes. The control...
Ieroham S. Baruch, Petia Georgieva, Josefina Barre...