Information Dynamics

The goal of the book is to provide a detailed and unified study of the flow of information in a quantitative manner, utilizing methods and techniques from information theory, time series analysis, nonlinear dynamics, and neural networks. The authors use analysis of test-bed simulations, empirical data, and real-world applications to give concrete perspectives and reinforcement for the key conceptual ideas and methods. The formulation provides a unique and consistent conceptual framework for the problem of discovering knowledge behind empirical data.

Topics and Features:

• self-contained presentations of concepts and methods
  
• interdisciplinary perspective
  
• dynamical characterization of time signals
  
• information flow and coarse graining
  
• real data applications
  
• coverage of temporal and spatiotemporal systems
  

Contents

• Introduction.
  
• Dynamical Systems Overview.
  
• Statistical Structure Extraction in Dynamical Systems: Parametric Formulation.
  
• Applications: Parametric Characterization of Time Series.
  
• Statistical Structure Extraction in Dynamical Systems: Nonparametric Formulation.
  
• Applications: Nonparametric Characterization of Time Series.
  
• Statistical Structure Extraction in Dynamical Systems: Semiparametric Formulation.
  
• Applications: Semiparametric Characterization of Time Series.
  
• Information Processing and Coding in Spatio-Temporal Dynamical Systems.
  
• Applications: Information Processing and Coding in Spatio-Temporal Dynamical Systems.
  
• Appendixes A,B,C,D.
  
• References.