A Neural Network Observer-Based Approach for Synchronization of Discrete-Time Chaotic Systems
نویسندگان
چکیده
This paper presents a new approach to solve synchronization problem of a large class of discrete chaotic systems. The chaotic systems can be reformulated as an appropriate class of linear parameter varying (LPV) systems. Then, based on the LPV representation, a neural network observer-based approach is proposed to solve the synchronization problem. The simulation results show the advantages of combining the LPV techniques and the neural networks to determine the appropriate observer gain within the context of chaotic system synchronization.
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