ESANN
2008
13 years 6 months ago
2008
Frequently, sequences of state transitions are triggered by specific signals. Learning these triggered sequences with recurrent neural networks implies storing them as different at...
IWANN
2001
Springer
13 years 9 months ago
2001
Springer
In the beginning of nineties, Hava Siegelmann proposed a new computational model, the Artificial Recurrent Neural Network (ARNN), and proved that it could perform hypercomputation....
SOFSEM
2004
Springer
13 years 10 months ago
2004
Springer
Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...
ROBOCUP
2005
Springer
13 years 10 months ago
2005
Springer
In this paper, a recurrent neural network is used to develop a dynamic controller for mobile robots. The advantage of the control approach is that no knowledge about the robot mode...
IDEAL
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Gaussian processes have been favourably compared to backpropagation neural networks as a tool for regression. We show that a recurrent neural network can implement exact ...
GECCO
2005
Springer
13 years 10 months ago
2005
Springer
In this paper, we propose a neuro-genetic stock prediction system based on financial correlation between companies. A number of input variables are produced from the relatively h...
VTC
2006
IEEE
13 years 11 months ago
2006
IEEE
Abstract—In this contribution, the application of fully connected recurrent neural networks (FCRNNs) is investigated in the context of narrowband channel prediction. Three differ...
IJCNN
2006
IEEE
13 years 11 months ago
2006
IEEE
— Cellular simultaneous recurrent neural network has been suggested to be a function approximator more powerful than the MLP’s, in particular for solving approximate dynamic pr...
IJCNN
2006
IEEE
13 years 11 months ago
2006
IEEE
—This paper investigates the application of a new kind of recurrent neural network called Echo State Networks (ESNs) for the problem of measuring the actual amount of harmonic cu...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. This paper presents Recurrent Policy Gradients, a modelfree reinforcement learning (RL) method creating limited-memory stochastic policies for partially observable Markov...