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Showing 1 to 2 of 2 for “"Adaptive dynamical networks"”.
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Classifying and Predicting Dynamics with Bioinspired Machine Learning
Artificial neural networks train by finding optimal weights, which are the strengths of connections between neuronal nodes. These optimal values are found by minimizing the error between the neural network’s output and what we know should be the true output for given inputs used during training. …
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Dynamics of adaptive recurrent neural networks
… is presented in the form of a slow-fast adaptive dynamical recurrent neural network. The plasticity rule is chosen from the class of Hebbian learning rules, in which the synaptic connection between two neurons evolves continuously as a function of their correlation in the recent past. …