The spectral radius remains a valid indicator of the echo state property for large reservoirsReport as inadecuate




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(2013)IEEE International Joint Conference on Neural Networks (IJCNN). Mark abstract In the field of Reservoir Computing, scaling the spectral radius of the weight matrix of a random recurrent neural network to below unity is a commonly used method to ensure the Echo State Property. Recently it has been shown that this condition is too weak. To overcome this problem, other more involved - sufficient conditions for the Echo State Property have been proposed. In this paper we provide a large-scale experimental verification of the Echo State Property for large recurrent neural networks with zero input and zero bias. Our main conclusion is that the spectral radius method remains a valid indicator of the Echo State Property; the probability that the Echo State Property does not hold, drops for larger networks with spectral radius below unity, which are the ones of practical interest.

Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-3153844



Author: Ken Caluwaerts, Francis wyffels , Sander Dieleman and Benjamin Schrauwen

Source: https://biblio.ugent.be/publication/3153844



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