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» The Recurrent Control Neural Network
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IJCNN
2008
IEEE
15 years 4 months ago
Robust adaptive control via neural linearization and four types of compensation
— In this paper, we propose a new type of neural adaptive control via dynamic neural networks. For a class of unknown nonlinear systems, a neural identifierFbased feedback linea...
Wen Yu, Xiaoou Li
NECO
2010
147views more  NECO 2010»
14 years 8 months ago
Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons
Abstract: Reservoir Computing (RC) systems are powerful models for online computations on input sequences. They consist of a memoryless readout neuron which is trained on top of a ...
Lars Büsing, Benjamin Schrauwen, Robert A. Le...
KES
2007
Springer
15 years 3 months ago
Making Financial Trading by Recurrent Reinforcement Learning
In this paper we propose a financial trading system whose strategy is developed by means of an artificial neural network approach based on a recurrent reinforcement learning algo...
Francesco Bertoluzzo, Marco Corazza
IJCNN
2006
IEEE
15 years 3 months ago
Reservoir-based techniques for speech recognition
— A solution for the slow convergence of most learning rules for Recurrent Neural Networks (RNN) has been proposed under the terms Liquid State Machines (LSM) and Echo State Netw...
David Verstraeten, Benjamin Schrauwen, Dirk Stroob...
ESANN
2008
14 years 11 months ago
Pruning and Regularisation in Reservoir Computing: a First Insight
Reservoir Computing is a new paradigm for using Recurrent Neural Networks which shows promising results. However, as the recurrent part is created randomly, it typically needs to b...
Xavier Dutoit, Benjamin Schrauwen, Jan M. Van Camp...