Chaos identification using variable structure recurrent neural networks
Ramón A. Félix, Edgar Nelson Sanchez · 2004
We present a new approach for chaos identification using variable structure recurrent neural networks (VSRNN) identification. A neural network identifier is presented, whose structure changes depending on its performance. In this way, a trade off between identification error and computational complexity is achieved.