Free shipping on orders over $95Buy one with 1% offer on sale price
Zoom the image with the mouse
Extracting Knowledge From Time Series: An Introduction to Nonlinear Empirical Modeling
ISBN:
9783642264825
List Price:
$54.99
Share:
Special Offers Available
Free shipping on orders over $95Buy one with 1% offer on sale priceBuy New
We can help you leverage the power of books
Customer Service
Connect with a dedicated account manager who is there every step of the way.
Price Match Guarantee
If you see better pricing elsewhere on your desired quantity, we will price match so you can be sure to get the best pricing.
Free Shipping
Enjoy free ground shipping on your order of $95 or more!
Brand New Guarantee
We only sell books that are brand new and protect that with a guarantee.
Customization
From author signatures to marketing inserts, custom packaging to brand stickers, we can help take your book marketing to the next level.
Details
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.
Product details
Need Books? Bookpal makes it easy
Connect With Us
Customer Reviews
Products related to this item
Related Products