Physical Review E, 75(4): pp. 066214-1 - 066214-9.When a low-dimensional chaotic attractor is embedded in a three-dimensional space its topological properties are embedding-dependent. We show that there are just three topological properties that depend on the embedding: Parity, global torsion, and knot type. We discuss how they can change with the embedding. Finally, we show that the mechanism that is responsible for creating chaotic behavior is an invariant of all embeddings. These results apply only to chaotic attractors of genus one, which covers the majority of cases in which experimental data have been subjected to topological analysis. This means that the conclusions drawn from previous analyses, for example that the mechanism generat...
The celebrated Takens' embedding theorem concerns embedding an attractor of a dynamical system in a ...
In this Ph.D. thesis we characterize the topology of chaotic attractors solution to set of different...
Abstract: The new technique for determining the embedding dimension for reconstructions...
We study an autonomous four-dimensional dynamical system used to model certain geophysical processes...
Embeddings are diffeomorphisms between some unseen physical attractor and a reconstructed image. Dif...
Topological chaxacterization is important in understanding the subtleties of chaotic behaviour. Unfo...
It is possible to compare results for the classical tests for embeddings of chaotic data with the re...
Topological chaxacterization is important in understanding the subtleties of chaotic behaviour. Unfo...
We extend the methods for topological analysis of chaotic dynamical systems in R^3 by introducing tw...
Using phase–plane analysis, findings from the theory of topological horseshoes and linked-twist maps...
A new approach to understanding nonlinear dynamics and strange attractors. The behavior of a physica...
It is possible to compare results for the classical tests for embeddings of chaotic data with the re...
This paper shows that the celebrated embedding theorem of Takens is a particular case of a much more...
Embeddings are diffeomorphisms between some dynamical phase space and a reconstructed image. Differe...
International audienceWhen a chaotic attractor is produced by a three-dimensional strongly dissipati...
The celebrated Takens' embedding theorem concerns embedding an attractor of a dynamical system in a ...
In this Ph.D. thesis we characterize the topology of chaotic attractors solution to set of different...
Abstract: The new technique for determining the embedding dimension for reconstructions...
We study an autonomous four-dimensional dynamical system used to model certain geophysical processes...
Embeddings are diffeomorphisms between some unseen physical attractor and a reconstructed image. Dif...
Topological chaxacterization is important in understanding the subtleties of chaotic behaviour. Unfo...
It is possible to compare results for the classical tests for embeddings of chaotic data with the re...
Topological chaxacterization is important in understanding the subtleties of chaotic behaviour. Unfo...
We extend the methods for topological analysis of chaotic dynamical systems in R^3 by introducing tw...
Using phase–plane analysis, findings from the theory of topological horseshoes and linked-twist maps...
A new approach to understanding nonlinear dynamics and strange attractors. The behavior of a physica...
It is possible to compare results for the classical tests for embeddings of chaotic data with the re...
This paper shows that the celebrated embedding theorem of Takens is a particular case of a much more...
Embeddings are diffeomorphisms between some dynamical phase space and a reconstructed image. Differe...
International audienceWhen a chaotic attractor is produced by a three-dimensional strongly dissipati...
The celebrated Takens' embedding theorem concerns embedding an attractor of a dynamical system in a ...
In this Ph.D. thesis we characterize the topology of chaotic attractors solution to set of different...
Abstract: The new technique for determining the embedding dimension for reconstructions...