Predicting the future : completing models of observed complex systems
Author(s)
Bibliographic Information
Predicting the future : completing models of observed complex systems
（Understanding complex systems / founding editor, J.A. Scott Kelso）
Springer, c2013
Available at / 5 libraries
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Library, Research Institute for Mathematical Sciences, Kyoto University数研
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Note
Includes bibliographical references (p. 227-232) and index
Description and Table of Contents
Description
Through the development of an exact path integral for use in transferring information from observations to a model of the observed system, the author provides a general framework for the discussion of model building and evaluation across disciplines. Through many illustrative examples drawn from models in neuroscience, geosciences, and nonlinear electrical circuits, the concepts are exemplified in detail. Practical numerical methods for approximate evaluations of the path integral are explored, and their use in designing experiments and determining a model's consistency with observations is explored.
Table of Contents
- Preface.- 1 An Overview
- The Challenge of Complex Systems.- 2 Examples as a Guide to the Issues.- 3 General Formulation of Statistical Data Assimilation.- 4 Evaluating the Path Integral.- 5 Twin Experiments.- 6 Analysis of Experimental Data.
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