Description
Regular Dynamics: Newton to Poincar; KAM Theorem | Bifurcations: Routes to Chaos, Stability and Instability | Reconstruction of Phase Space: Regular and Chaotic Motions; Observed Chaos | Choosing Time Delays: Chaos as an Information Source; Average Mutual Information. | Choosing the Dimension of Reconstructed Phase Space | Invariants of the Motion: Global & Local Lyapunov Exponents; Lorenz Model | Modeling Chaos: Local & Global Models; Phase Space Models | Signal Separation: Probabilistic Cleaning; “Blind” Signal Separation | Control and Chaos: Parametric Control; Examples of Control (including magnetoelastic ribbon, electric circuits, cardiac tissue) | Synchronization of Chaotic Systems: Identical or Dissimilar Systems; Chaotic Nonlinear Circuits | Other Example Systems: Laser Intensity Fluctuations; Volume Fluctuations of the Great Salt Lake; Motion in a Fluid Boundary Layer | Estimating in Chaos: Cramr-Rao Bounds | The Chaos Toolkit: Making “Physics” out of Chaos
