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» Optimal spontaneous activity in neural network modeling
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IJIT
2004
14 years 11 months ago
Modeling of Pulping of Sugar Maple Using Advanced Neural Network Learning
This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sa...
GECCO
2005
Springer
204views Optimization» more  GECCO 2005»
15 years 3 months ago
Modeling systems with internal state using evolino
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
Daan Wierstra, Faustino J. Gomez, Jürgen Schm...
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
14 years 11 months ago
A hybrid method for tuning neural network for time series forecasting
This paper presents an study about a new Hybrid method GRASPES - for time series prediction, inspired in F. Takens theorem and based on a multi-start metaheuristic for combinatori...
Aranildo Rodrigues Lima Junior, Tiago Alessandro E...
IJCNN
2000
IEEE
15 years 2 months ago
Robust Adaptive Critic Based Neurocontrollers for Systems with Input Uncertainties
A two-neural network approach to solving nonlinear optimal control problems is described in this study. This approach called the adaptive critic method consists of one neural netw...
Zhongwu Huang, S. N. Balakrishnan
NC
1998
140views Neural Networks» more  NC 1998»
14 years 11 months ago
Recurrent Neural Networks with Iterated Function Systems Dynamics
We suggest a recurrent neural network (RNN) model with a recurrent part corresponding to iterative function systems (IFS) introduced by Barnsley 1] as a fractal image compression ...
Peter Tiño, Georg Dorffner