… Neural Networks, to Chaotic Dynamical systems, with particular focus on dynamics reconstruction
and parameter estimation. … The robustness of this approach derives from the fact that …

… stochastic and deterministic chaotic dynamical systems in noise. … The robustness and scalability
of our approach is evaluated … problem of estimating the state variables of the system from …

… The Lyapunov Time is a key time scale in chaotic dynamical systems, which is defined as
the inverse of the leading Lyapunov exponent Λ of the system, which, in turn, is the exponential …

… properties of neural networks and dynamical systems theory. … close network trajectories
typically show strong divergences (… , along with an estimation of its autocorrelation function, for a …

… The multi-step ahead forecasting of a chaotic dynamic is usually … LSTM nets also proved
more robust with respect to the … -time dynamical systems, universally known for being chaotic, to …

… of a high-dimensional differentiable dynamical system [40]. … for all dimensionality estimates
growth of dimension with g in … a strong effect of time-discretization: Increasing the step size …

… chaotic system. In the last few years, only a few works related with 4D chaotic dynamical
systems … m and r has a strong impact on the entropy estimates obtained by these three indices. …

… metrics adopted for their performance evaluation, and the details of the training procedure. …
neural networks are dynamical system which are know to frequently exhibit a chaotic …

… dynamical systems from data. Emphasis is placed on predictions at long times, with limited
data availability. Inspired by global stability analysis, and the observation of strong … evaluation…

… (SE-NST2FNN) is proposed for the estimation of the unknown functions in the … neural
networks, the proposed SE-NST2FNN is used for the identification of nonlinear dynamic systems. …