Multiobjective synchronization of coupled systems
Copyright policy )Multiobjective synchronization of coupled systems
In this paper, multiobjective synchronization of chaotic systems is investigated by especially simultaneously minimizing optimization of control cost and convergence speed. The coupling form and coupling strength are optimized by an improved multiobjective evolutionary approach that includes a hybrid chromosome representation. The hybrid encoding scheme combines binary representation with real number representation. The constraints on the coupling form are also considered by converting the multiobjective synchronization into a multiobjective constraint problem. In addition, the performances of the adaptive learning method and non-dominated sorting genetic algorithm-II as well as the effectiveness and contributions of the proposed approach are analyzed and validated through the Rössler system in a chaotic or hyperchaotic regime and delayed chaotic neural networks.
- Leibniz Association Germany
- Potsdam-Institut für Klimafolgenforschung (Potsdam Institute for Climate Impact Research) Germany
- Brunel University London United Kingdom
- Hong Kong Polytechnic University (香港理工大學) China (People's Republic of)
- Potsdam Institute for Climate Impact Research Germany
Learning (artificial intelligence), Cellular biophysics, Complex networks, Neural nets, Learning and adaptive systems in artificial intelligence, Synchronization of solutions to ordinary differential equations, Neural networks for/in biological studies, artificial life and related topics, 530, Sychronisation, Complex behavior and chaotic systems of ordinary differential equations, Qualitative investigation and simulation of ordinary differential equation models, Chaos
Learning (artificial intelligence), Cellular biophysics, Complex networks, Neural nets, Learning and adaptive systems in artificial intelligence, Synchronization of solutions to ordinary differential equations, Neural networks for/in biological studies, artificial life and related topics, 530, Sychronisation, Complex behavior and chaotic systems of ordinary differential equations, Qualitative investigation and simulation of ordinary differential equation models, Chaos
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