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Consistency is an extension to generalized synchronization which quantifies the degree of functional dependency of a driven nonlinear system to its input. We apply this concept to echo-state networks, which are an artificial-neural network version of reservoir computing. Through a replica test, we measure the consistency levels of the high-dimensional response, yielding a comprehensive portrait of the echo-state property.
|Number of pages||9|
|Journal||Chaos: an interdisciplinary journal of nonlinear science|
|Publication status||Published - 1 Feb 2019|