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Found 5 papers, 0 papers with code
Analyzing Echo-state Networks Using Fractal Dimension
This connection between fractal dimension and network connectivity is an interesting new direction for recurrent neural network initialization and reservoir computing.
Critical Echo State Networks that Anticipate Input using Morphable Transfer Functions
The paper investigates a new type of truly critical echo state networks where individual transfer functions for every neuron can be modified to anticipate the expected next input.
Orthogonal Echo State Networks and stochastic evaluations of likelihoods
We report about probabilistic likelihood estimates that are performed on time series using an echo state network with orthogonal recurrent connectivity.
Echo State Condition at the Critical Point
Recurrent networks with transfer functions that fulfill the Lipschitz continuity with K=1 may be echo state networks if certain limitations on the recurrent connectivity are applied.
Input anticipating critical reservoirs show power law forgetting of unexpected input events
Usually, reservoir computing shows an exponential memory decay.
