Using Neural Models for Analyzing Time Series
نویسنده
چکیده
We demonstrate the use of neural networks to model and analyze time series of nonlinear dynamical systems. Based on recent results concerning the embedding of attractors from scalar time series, we use the neural models to estimate the embedding dimension and the nonnegative Lyapunov exponents of the system.
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تاریخ انتشار 2007