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Nonlinear dynamical systems control using a new RNN temporal learning strategy

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2 Author(s)
Yong Fang ; Dept. of Electron. Eng., City Univ. of Hong Kong, China ; Chow, T.W.S.

The ability of recurrent neural networks (RNN) to handle time-varying input/output through its own temporal operation is discussed. A new class of continuous-time (CT) RNN is proposed and it is proved that any finite time trajectory of a given n-dimensional dynamical CT system with input can be approximated by the internal state of the output units of an RNN. The proposed RNNs are extended for temporal processing.

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Circuits and Systems II: Express Briefs, IEEE Transactions on  (Volume:52 ,  Issue: 11 )