Nonlinear Analysis of Time Series Data
Henry D. I. Abarbanel, Ulrich Parlitz · 2006
This chapter contains sections titled: Introduction Unfolding the Data: Embedding Theorem in Practice Choosing T: Average Mutual Information Choosing D: False Nearest Neighbors Local or Dynamical Dimension Interspike Intervals Where are We? Lyapunov Exponents: Prediction, Classification, and Chaos Predicting Modeling Modeling Interspike Intervals Modeling the Observed Membrane Voltage Time Series ODE Modeling Conclusion References