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Understanding Complex Systems Ser.: Predicting the Future : Completing Models of Observed Complex Systems by Henry D. I. Abarbanel (2013, Hardcover)
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About this product
Product Identifiers
PublisherSpringer New York
ISBN-101461472172
ISBN-139781461472179
eBay Product ID (ePID)167603290
Product Key Features
Number of PagesXvi, 238 Pages
Publication NamePredicting the Future : Completing Models of Observed Complex Systems
LanguageEnglish
Publication Year2013
SubjectComputer Simulation, System Theory, Physics / Mathematical & Computational, Complex Analysis
TypeTextbook
AuthorHenry D. I. Abarbanel
Subject AreaMathematics, Computers, Science
SeriesUnderstanding Complex Systems Ser.
FormatHardcover
Dimensions
Item Weight179.5 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
Number of Volumes1 vol.
IllustratedYes
Table Of ContentPreface.- 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.
SynopsisThis book discusses model building and evaluation across disciplines, by means of an exact path integral for transferring information from observations to a model of the observed system. Offers examples in geosciences, nonlinear electrical circuits and more., 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., 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.
LC Classification NumberQ295
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