skip to content

Neural networks for nonlinear modeling of dynamic systems: Design problems

Wednesday 20th July 2011 - 10:30 to 11:00
INI Seminar Room 1
We start from a brief review of artificial neural networks with external dynamics as models for nonlinear dynamic systems (NARX, NFIR). We discuss problems arising in designing of such networks. In particular, we put emphasis on active learning, i.e., on iterative improvements of the Fisher information matrix. Furthermore, we propose random projections (applied to input and/or output signals) for increasing the robustness of model selection process.
The video for this talk should appear here if JavaScript is enabled.
If it doesn't, something may have gone wrong with our embedded player.
We'll get it fixed as soon as possible.
Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons