Nonlinear Modeling and Forecasting
Table of Contents
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Edited by Martin Casdagli and Stephen Eubank
Preface
Function Approximation
Tesselations and Dynamical Systems
Supervised Learning: A Theoretical Framework
Prediction of Chaotic Time Series using CNLS-Net-Example: The Mackey-Glass Equation
Forecasting with Weighted Maps
Multivariate Function and Operator Estimation, Based on Smoothing Splines and Reproducing Kernels
Statistics
Optimal Estimation of Fractal Dimension
Diagnostic Testing for Nonlinearity, Chaos, and General Dependence in Time-Series Data
Using Surrogate Data to Detect Nonlinearity in Time Series
Experiments in Modeling Nonlinear Relationships Between Time Series
Analysis of Nonlinear Time Series (and Chaos) by Bispectral Methods
Dynamical System
Local and Global Lyapunov Exponents on a Strange Attractor
Local Forecasting of High-Dimensional Chaotic Dynamics
A Dynamical Systems Approach to Modeling Input-Output Systems
Identification and Filtering of Nonlinear Systems Using Canonical Variate Analysis
Forecasting Probabilities with Neural Networks
Semantics and Thermodynamics
Use of Recurrence Plots in the Analysis of Time-Sereis Data
Applications
Nonlinear Forecasts for the S&P Stock Index
Predicting Sunspots and Exchange Rates with Connectionist Networks
Nonlinear Prediction of Speech Signals
Application of Nonlinear Prediction to Signal Separation
Application of Nonlinear Time-Series Models to Driven Systems
Periodic Saddle Orbits in Experimental Strange Attractors
Memory-Based Approaches to Approximating Continuous Functions
Index |
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