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Extracting Knowledge From Time Series - An Introduction to Nonlinear Empirical Modeling (Paperback, 2010 ed.) Loot Price: R1,562
Discovery Miles 15 620
Extracting Knowledge From Time Series - An Introduction to Nonlinear Empirical Modeling (Paperback, 2010 ed.): Boris P....

Extracting Knowledge From Time Series - An Introduction to Nonlinear Empirical Modeling (Paperback, 2010 ed.)

Boris P. Bezruchko, Dmitry A. Smirnov

Series: Springer Series in Synergetics

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Loot Price R1,562 Discovery Miles 15 620 | Repayment Terms: R146 pm x 12*

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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.

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Springer Series in Synergetics
Release date: November 2012
First published: 2010
Authors: Boris P. Bezruchko • Dmitry A. Smirnov
Dimensions: 235 x 155 x 22mm (L x W x T)
Format: Paperback
Pages: 410
Edition: 2010 ed.
ISBN-13: 978-3-642-26482-5
Categories: Books > Business & Economics > Economics > Economic theory & philosophy
Books > Business & Economics > Finance & accounting > General
Books > Professional & Technical > Environmental engineering & technology > General
Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics
Books > Science & Mathematics > Physics > Applied physics & special topics > Geophysics
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LSN: 3-642-26482-4
Barcode: 9783642264825

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