ShopSpell

Extracting Knowledge From Time Series: An Introduction to Nonlinear Empirical Modeling [Hardcover]

$41.99     $54.99    24% Off      (Free Shipping)
100 available
  • Category: Books (Science)
  • Author:  Bezruchko, Boris P., Smirnov, Dmitry A.
  • Author:  Bezruchko, Boris P., Smirnov, Dmitry A.
  • ISBN-10:  3642126006
  • ISBN-10:  3642126006
  • ISBN-13:  9783642126000
  • ISBN-13:  9783642126000
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  350
  • Pages:  350
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Feb-2010
  • Pub Date:  01-Feb-2010
  • SKU:  3642126006-11-SPRI
  • SKU:  3642126006-11-SPRI
  • Item ID: 105251150
  • List Price: $54.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Oct 04 to Oct 06
  • Notes: Brand New Item. Not shipped to AK, HI, APO, FPO, AE.
Mathematical modelling is ubiquitous. Almost every book in exact science touches on mathematical models of a certain class of phenomena, on more or less speci?c approaches to construction and investigation of models, on their applications, etc. As many textbooks with similar titles, Part I of our book is devoted to general qu- tions of modelling. Part II re?ects our professional interests as physicists who spent much time to investigations in the ?eld of non-linear dynamics and mathematical modelling from discrete sequences of experimental measurements (time series). The latter direction of research is known for a long time as system identi?cation in the framework of mathematical statistics and automatic control theory. It has its roots in the problem of approximating experimental data points on a plane with a smooth curve. Currently, researchers aim at the description of complex behaviour (irregular, chaotic, non-stationary and noise-corrupted signals which are typical of real-world objects and phenomena) with relatively simple non-linear differential or difference model equations rather than with cumbersome explicit functions of time. In the second half of the twentieth century, it has become clear that such equations of a s- ?ciently low order can exhibit non-trivial solutions that promise suf?ciently simple modelling of complex processes; according to the concepts of non-linear dynamics, chaotic regimes can be demonstrated already by a third-order non-linear ordinary differential equation, while complex behaviour in a linear model can be induced either by random in?uence (noise) or by a very high order of equations.Models And Forecast.- The Concept of Model. What is Remarkable in Mathematical Models.- Two Approaches to Modelling and Forecast.- Dynamical (Deterministic) Models of Evolution.- Stochastic Models of Evolution.- Modeling From Time Series.- Problem Posing in Modelling from Data Series.- Data Series as a Source for Modelling.- Restoration of Explicit ls+
Add Review