Learning a simple recurrent neural state space model to behave like Chua's double scroll

The authors present a simple discrete time autonomous neural state space model (recurrent network) that behaves like Chua's double scroll. The model is identified using Narendra's dynamic back propagation procedure. Learning is done in "packets" of increasing time horizon.<
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