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ESANN
2004

Input Space Bifurcation Manifolds of RNNs

9 years 11 months ago
Input Space Bifurcation Manifolds of RNNs
We derive analytical expressions of local codim-1-bifurcations for a fully connected, additive, discrete-time RNN, where we regard the external inputs as bifurcation parameters. The complexity of the bifurcation diagrams obtained increases exponentially with the number of neurons. We show that a three-neuron cascaded network can serve as a universal oscillator, whose amplitude and frequency can be completely controlled by input parameters.
Robert Haschke, Jochen J. Steil
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2004
Where ESANN
Authors Robert Haschke, Jochen J. Steil
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