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

By: Boris P. Bezruchko and Dmitry A. Smirnov

Sign Up Now! Already a Member? Log In
You must be logged into Bookshare to access this title. Learn about membership options, or view our freely available titles.

Synopsis: 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.

Book Quality:: Publisher Quality
ISBN-13:: 9783642126017
Related ISBNs:: 9783642126000
Publisher:: Springer Berlin Heidelberg
Date of Addition:: 11/18/16
Copyrighted By:: Springer
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Science, Business and Finance, Earth Sciences, Mathematics and Statistics
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.