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Regularization of the Trajectories of Dynamical Systems by Adjusting Parameters
Abstract:A gradient learning method to regulate the trajectories of some nonlinear chaotic systems is proposed. The method is motivated by the gradient descent learning algorithms for neural networks. It is based on two systems: dynamic optimization system and system for finding sensitivities. Numerical results of several examples are presented, which convincingly illustrate the efficiency of the method.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1335520Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1094
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