Optimization of dynamic neural fields

[1]  Estela Bicho,et al.  Target Representation on an Autonomous Vehicle with Low-Level Sensors , 2000, Int. J. Robotics Res..

[2]  Paul J. Werbos,et al.  Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.

[3]  Eitaro Aiyoshi,et al.  A distributed model of the saccade system: simulations of temporally perturbed saccades using position and velocity feedback , 1999, Neural Networks.

[4]  Barak A. Pearlmutter Gradient calculations for dynamic recurrent neural networks: a survey , 1995, IEEE Trans. Neural Networks.

[5]  P. Hartman Ordinary Differential Equations , 1965 .

[6]  Michael A. Arbib,et al.  The handbook of brain theory and neural networks , 1995, A Bradford book.

[7]  Kenji Doya,et al.  Recurrent networks: supervised learning , 1998 .

[8]  Xin Yao,et al.  Evolving artificial neural networks , 1999, Proc. IEEE.

[9]  G. Schöner,et al.  The Dynamic Neural Field Theory of Motor Programming: Arm and Eye Movements , 1997 .

[10]  M. Giese Dynamic neural field theory for motion perception , 1998 .

[11]  Pietro G. Morasso,et al.  Self-Organization, Computational Maps, and Motor Control , 1997 .

[12]  J. G. Taylor,et al.  Neural ‘bubble’ dynamics in two dimensions: foundations , 1999, Biological Cybernetics.

[13]  Amir C. Akhavan,et al.  Parametric Population Representation of Retinal Location: Neuronal Interaction Dynamics in Cat Primary Visual Cortex , 1999, The Journal of Neuroscience.

[14]  Werner von Seelen,et al.  Complex behavior by means of dynamical systems for an anthropomorphic robot , 1999, Neural Networks.

[15]  G. Schöner,et al.  The distribution of neuronal population activation (DPA) as a tool to study interaction and integration in cortical representations , 1999, Journal of Neuroscience Methods.

[16]  Guo-Zheng Sun,et al.  Green's Function Method for Fast On-Line Learning Algorithm of Recurrent Neural Networks , 1991, NIPS.

[17]  William H. Press,et al.  Numerical recipes in C , 2002 .

[18]  S. Amari,et al.  Existence and stability of local excitations in homogeneous neural fields , 1979, Journal of mathematical biology.

[19]  Ronald J. Williams,et al.  A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.

[20]  Thomas Bäck,et al.  An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.

[21]  Nikolaus Hansen,et al.  Completely Derandomized Self-Adaptation in Evolution Strategies , 2001, Evolutionary Computation.