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IJON
1998
107views more  IJON 1998»
13 years 4 months ago
Training wavelet networks for nonlinear dynamic input-output modeling
In the framework of nonlinear process modeling, we propose training algorithms for feedback wavelet networks used as nonlinear dynamic models. An original initialization procedure...
Yacine Oussar, Isabelle Rivals, Léon Person...
ICANN
2009
Springer
13 years 9 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
RAS
2002
168views more  RAS 2002»
13 years 4 months ago
Neural predictive control for a car-like mobile robot
: This paper presents a new path-tracking scheme for a car-like mobile robot based on neural predictive control. A multi-layer back-propagation neural network is employed to model ...
Dongbing Gu, Huosheng Hu
AAAI
2012
11 years 6 months ago
Goal Recognition with Markov Logic Networks for Player-Adaptive Games
Goal recognition in digital games involves inferring players’ goals from observed sequences of low-level player actions. Goal recognition models support player-adaptive digital ...
Eun Y. Ha, Jonathan P. Rowe, Bradford W. Mott, Jam...
IJCNN
2007
IEEE
13 years 10 months ago
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks
— A single biological neuron is able to perform complex computations that are highly nonlinear in nature, adaptive, and superior to the perceptron model. A neuron is essentially ...
Manish Saggar, Tekin Meriçli, Sari Andoni, ...