zbMATH — the first resource for mathematics

Geometry Search for the term Geometry in any field. Queries are case-independent.
Funct* Wildcard queries are specified by * (e.g. functions, functorial, etc.). Otherwise the search is exact.
"Topological group" Phrases (multi-words) should be set in "straight quotation marks".
au: Bourbaki & ti: Algebra Search for author and title. The and-operator & is default and can be omitted.
Chebyshev | Tschebyscheff The or-operator | allows to search for Chebyshev or Tschebyscheff.
"Quasi* map*" py: 1989 The resulting documents have publication year 1989.
so: Eur* J* Mat* Soc* cc: 14 Search for publications in a particular source with a Mathematics Subject Classification code (cc) in 14.
"Partial diff* eq*" ! elliptic The not-operator ! eliminates all results containing the word elliptic.
dt: b & au: Hilbert The document type is set to books; alternatively: j for journal articles, a for book articles.
py: 2000-2015 cc: (94A | 11T) Number ranges are accepted. Terms can be grouped within (parentheses).
la: chinese Find documents in a given language. ISO 639-1 language codes can also be used.

a & b logic and
a | b logic or
!ab logic not
abc* right wildcard
"ab c" phrase
(ab c) parentheses
any anywhere an internal document identifier
au author, editor ai internal author identifier
ti title la language
so source ab review, abstract
py publication year rv reviewer
cc MSC code ut uncontrolled term
dt document type (j: journal article; b: book; a: book article)
Detecting coupling in the presence of noise and nonlinearity. (English) Zbl 1268.62129
Schelter, Björn (ed.) et al., Handbook of time series analysis: Recent theoretical developments and applications. Weinheim: Wiley-VCH (ISBN 978-3-527-40623-4/hbk; 978-3-527-60997-0/ebook). 265-282 (2006).
Summary: Establishing the presence of coupling and interactions in weakly coupled systems, especially in the presence of noise and nonlinearity, is a difficult problem. We explore different measures to detect a relationship between two systems. We compare the sensitivity of the different measures to stochastic coupled systems, discontinuous chaotic systems and continuous chaotic systems. We then test the robustness of the detection of coupling in the presence of additive noise. In conclusion, we find that nonlinear methods are more sensitive to detecting coupling under ideal conditions. However, in the presence of noise, linear techniques are more robust. For the entire collection see [Zbl 1104.62328].

62M99Inference from stochastic processes
37N99Applications of dynamical systems
37D45Strange attractors, chaotic dynamics