Web: http://arxiv.org/abs/2107.08399

Jan. 14, 2022, 2:11 a.m. | Andrei Velichko, Hanif Heidari

cs.LG updates on arXiv.org arxiv.org

Measuring the predictability and complexity of time series using entropy is
essential tool de-signing and controlling a nonlinear system. However, the
existing methods have some drawbacks related to the strong dependence of
entropy on the parameters of the methods. To overcome these difficulties, this
study proposes a new method for estimating the entropy of a time series using
the LogNNet neural network model. The LogNNet reservoir matrix is filled with
time series elements according to our algorithm. The accuracy of the
classification of images from the MNIST-10 database is considered …

artificial arxiv entropy for networks neural neural networks time time series

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