Logo - springer
Slogan - springer

Physics - Complexity | Extracting Knowledge From Time Series - An Introduction to Nonlinear Empirical Modeling

Extracting Knowledge From Time Series

An Introduction to Nonlinear Empirical Modeling

Bezruchko, Boris P., Smirnov, Dmitry A.

2010, XXII, 410 p.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$99.00

(net) price for USA

ISBN 978-3-642-12601-7

digitally watermarked, no DRM

Included Format: PDF and EPUB

download immediately after purchase


learn more about Springer eBooks

add to marked items

Hardcover
Information

Hardcover version

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$124.00

(net) price for USA

ISBN 978-3-642-12600-0

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$124.00

(net) price for USA

ISBN 978-3-642-26482-5

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • Useful as a self-study guide
  • Provides a modern approach and practical examples
  • Written by well known authors with many contribution to the field
This book addresses the fundamental question of how to construct mathematical models for the evolution of dynamical systems from experimentally-obtained time series. It places emphasis on chaotic signals and nonlinear modeling and discusses different approaches to the forecast of future system evolution. In particular, it teaches readers how to construct difference and differential model equations depending on the amount of a priori information that is available on the system in addition to the experimental data sets. This book will benefit graduate students and researchers from all natural sciences who seek a self-contained and thorough introduction to this subject.

Content Level » Research

Keywords » Stochastic model - Stochastic models - chaotic signals - model equations - modeling - modeling and forecast - nonlinear dynamical systems - sets - time series analysis

Related subjects » Complexity - Environmental Engineering and Physics - Game Theory / Mathematical Methods - Geophysics & Geodesy - Quantitative Finance

Table of contents / Preface / Sample pages 

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Statistical Physics, Dynamical Systems and Complexity.