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Identification of Complex Dynamical Systems with Neural Networks (1/2)
<!--HTML--><p>The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of t...
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| Lenguaje: | eng |
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2016
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| Acceso en línea: | http://cds.cern.ch/record/2237701 |