Open AccessESTIMATION OF THE LYAPUNOV SPECTRUM FROM ONE-DIMENSIONAL OBSERVATIONS USING NEURAL NETWORKS
Author(s) -
Vladimir Golovko
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.2.2.201
Subject(s) - attractor , lyapunov function , artificial neural network , computer science , spectrum (functional analysis) , dynamical systems theory , lyapunov exponent , dynamical system (definition) , multilayer perceptron , perceptron , mathematics , series (stratigraphy) , state (computer science) , control theory (sociology) , statistical physics , algorithm , artificial intelligence , chaotic , physics , mathematical analysis , control (management) , nonlinear system , paleontology , quantum mechanics , biology
This paper discusses the neural network approach for computing of Lyapunov spectrum using one dimensional time series from unknown dynamical system. Such an approach is based on the reconstruction of attractor dynamics and applying of multilayer perceptron (MLP) for forecasting the next state of dynamical system from the previous one. It allows for evaluating the Lyapunov spectrum of unknown dynamical system accurately and efficiently only by using one observation. The results of experiments are discussed.