Inference of functional dependence in coupled chaotic systems using feed-forward neural network
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We propose a new model-free method based on feed-forward artificial neuronal network for detecting functional connectivity in coupled systems. The developed method which does not require large computational costs and which is able to work with short data trials can be used for analysis and restoration of connectivity in experimental multichannel data of different nature. We test this approach on the chaotic Rossler system and demonstrate good agreement with the previous well-know results.