Echo State Networks trained by Tikhonov least squares are L2(μ) approximators of ergodic dynamical systems

14 May 2020Allen G HartJames L HookJonathan H P Dawes

Echo State Networks (ESNs) are a class of single-layer recurrent neural networks with randomly generated internal weights, and a single layer of tuneable outer weights, which are usually trained by regularised linear least squares regression. Remarkably, ESNs still enjoy the universal approximation property despite the training procedure being entirely linear... (read more)

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