8 citations · 12 across the 7 of their papers we have counts for
5 papers · 1 filter
Analyzing Echo-state Networks Using Fractal Dimension
Norbert Michael Mayer, Oliver Obst
This work joins aspects of reservoir optimization, information-theoretic optimal encoding, and at its center fractal analysis. We build on the observation that, due to the recursiv…
Critical Echo State Networks that Anticipate Input using Morphable Transfer Functions
Norbert Michael Mayer
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
Norbert Michael Mayer, Ying-Hao Yu
We report about probabilistic likelihood estimates that are performed on time series using an echo state network with orthogonal recurrent connectivity. The results from tests usin…
Echo State Condition at the Critical Point
Norbert Michael Mayer
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 applie…
Input anticipating critical reservoirs show power law forgetting of unexpected input events
Norbert Michael Mayer
Usually, reservoir computing shows an exponential memory decay. This paper investigates under which circumstances echo state networks can show a power law forgetting. That means tr…