200 search results - page 13 / 40 » A Nonlinear Predictive State Representation |
ICPR
2010
IEEE
13 years 6 months ago
2010
IEEE
Abstract—Learning dynamical systems is one of the important problems in many fields. In this paper, we present an algorithm for learning non-linear dynamical systems which works...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
We present an algorithm for on-line, incremental discovery of temporal-difference (TD) networks. The key contribution is the establishment of three criteria to expand a node in TD...
ICANN
2009
Springer
14 years 4 days ago
2009
Springer
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
NECO
2007
13 years 7 months ago
2007
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
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...