Trends in Neurocomputing at ESANN 2004. Neurocomputing. 64:1–4.. 2005.
Backpropagation-Decorrelation: online recurrent learning with O(N) complexity. Proc. Int. Joint Conference Neural Networks. 1:843–848.. 2004.
Input Space Bifurcation Manifolds of RNNs. Proc. European Symposium Artificial Neural Networks. :13–19.. 2004.
Neural Dynamics for Task-Oriented Grouping of Communicating Agents. Proc. European Symposium Artificial Neural Networks. :531–536.. 2004.
Situated robot learning for multi-modal instruction and imitation of grasping. Robotics and Autonomous Systems. 47:129–141.. 2004.
Architekturen situierter Kommunikatoren: Von Perzeption über Kognition zum Lernen. Informatik 2003 - Innovative Informatikanwendungen. 2:29–44.. 2003.
Learning Compatibitlity Functions for Feature Binding and Perceptual Grouping. Proc. of Int. Conference Artificial Neural Networks. LNCS 2714:60–67.. 2003.
Neural Architectures for Robotic Intelligence. Reviews in the Neurosciences. 14:121–143.. 2003.
A Neural Network Model that Calculates Dynamic Distance Transform for Path Planning and Exploration in a Changing Environment. Proc. IEEE Int. Conf. on Robotics and Automation. :4209–4214.. 2003.
Real Time Path Planning in Dynamic Environment: a Comparison of Three Neural Network Models. Proc. IEEE Int. Conf. Systems, Man, and Cybernetics. :3408–3413.. 2003.
Static Sliding Mode Phenomena in Dynamical Systems. IEEE Trans. Automatic Control. 48:680–686.. 2003.
On the weight dynamcis of recurrent learning. Proc. European Symposium Artificial Neural Networks. :73–78.. 2003.
Data Driven Generation of Interactions for Feature Bindingand Relaxation Labeling. Proc. Int. Conf. Artificial Neural Networks. :432–437.. 2002.
Local structural stability of recurrent networks with time-varying weights. Neurocomputing. 48:39–51.. 2002.
Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks. Proc. Int. Conf. Intelligent Robotis and Systems. :1082–1089.. 2002.
A New Wave Neural Network Dynamics for Planning Safe Paths of Autonomous Objects in a Dynamically Changing World. Advances in Neural Networks World. :141–146.. 2002.
Perspectives on Learning with Recurrent Neural Networks. Proc. European Symposium Artificial Neural Networks. :357–368.. 2002.
A Competitive Layer Model for Feature Binding and Sensory Segmentation. Neural Computation. 13:357–387.. 2001.
Controlling oscillatory behaviour of a two neuron recurrent neural network using inputs. Artificial Neural Networks - ICANN 2001. 2130:1109–1114.. 2001.
Guiding Attention for Grasping Tasks by Gestural Instruction: The GRAVIS-Robot Architecture. Proc. Int. Conf. Intelligent Robots and Sytems. :1570–1577.. 2001.
Local input-output stability of recurrent networks with time-varying weights. Proc. European Symposium Artificial Neural Networks. :281–286.. 2000.
Robust control in closed loops realised by fast signal transmission of infinite gain neurons. Proc. Int. Conf. Artificial Neural Networks. 1:260–266.. 2000.
Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. Proc. European Symposium Artificial Neural Networks. :369–374.. 1999.
Recurrent Learning of Input-Output Stable Behaviour in Function Space: A Case Study with the Roessler Attractor. Proc. Int. Conf. Artificial Neural Networks. :761–766.. 1999.