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TNN
2010
14 years 4 months ago
2010
Abstract--Recurrent neural networks have become a prominent tool for optimizations including linear or nonlinear variational inequalities and programming, due to its regular mathem...
ICANN
2010
Springer
14 years 11 months ago
2010
Springer
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
ESANN
2004
14 years 11 months ago
2004
To emphasize the electrical nature of information processing in the brain we use a compartmental model of single neurons. The realistic simulation of wave-like activity in the recu...
ESANN
2000
14 years 11 months ago
2000
Abstract. We present local conditions for input-output stability of recurrent neural networks with time-varying parameters introduced for instance by noise or on-line adaptation. T...
GECCO
2003
Springer
15 years 3 months ago
2003
Springer
Continuous Time Recurrent Neural Networks (CTRNNs) have previously been proposed as an enabling paradigm for evolving analog electrical circuits to serve as controllers for physica...