TY  - JOUR
A1  - Zou, Yong
A1  - Thiel, M.
A1  - Romano, Maria Carmen
A1  - Kurths, Jürgen
A1  - Bi, Q.
T1  - Shrimp structure and associated dynamics in parametrically excited oscillators
JF  - International journal of bifurcation and chaos : in applied sciences and engineering
N2  - We investigate the bifurcation structures in a two-dimensional parameter space (PS) of a parametrically excited system with two degrees of freedom both analytically and numerically. By means of the Renyi entropy of second order K-2, which is estimated from recurrence plots, we uncover that regions of chaotic behavior are intermingled with many complex periodic windows, such as shrimp structures in the PS. A detailed numerical analysis shows that, the stable solutions lose stability either via period doubling, or via intermittency when the parameters leave these shrimps in different directions, indicating different bifurcation properties of the boundaries. The shrimps of different sizes offer promising ways to control the dynamics of such a complex system.
KW  - bifurcation analysis
KW  - recurrence plot
KW  - period doubling
KW  - intermittency
Y1  - 2006
U6  - https://doi.org/10.1142/S0218127406016987
SN  - 0218-1274
VL  - 16
IS  - 12
SP  - 3567
EP  - 3579
PB  - World Scientific Publ. Co
CY  - Singapore
ER  - 
TY  - JOUR
A1  - Donges, Jonathan Friedemann
A1  - Zou, Yong
A1  - Marwan, Norbert
A1  - Kurths, Jürgen
T1  - Complex networks in climate dynamics : comparing linear and nonlinear network construction methods
N2  - Complex network theory provides a powerful framework to statistically investigate the topology of local and non- local statistical interrelationships, i.e. teleconnections, in the climate system. Climate networks constructed from the same global climatological data set using the linear Pearson correlation coefficient or the nonlinear mutual information as a measure of dynamical similarity between regions, are compared systematically on local, mesoscopic and global topological scales. A high degree of similarity is observed on the local and mesoscopic topological scales for surface air temperature fields taken from AOGCM and reanalysis data sets. We find larger differences on the global scale, particularly in the betweenness centrality field. The global scale view on climate networks obtained using mutual information offers promising new perspectives for detecting network structures based on nonlinear physical processes in the climate system.
Y1  - 2009
UR  - http://www.springerlink.com/content/1951-6355
U6  - https://doi.org/10.1140/epjst/e2009-01098-2
SN  - 1951-6355
ER  -