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Seminar: Dynamics of Adaptive Networks - Summer Term 2019

Lupe

LV-Nr. 3233 L 606

Prof. Dr. Eckehard Schöll, PhD
Dr. Anna Zakharova
Dr. Iryna Omelchenko

Time: Tuesday 16:15 (c.t.) 
Room: EW 731
Begin: 09.04.2019

Durch den Besuch der Veranstaltung mit Vortrag und Ausarbeitung können 5 ECTS Punkte erworben werden.

The seminar offers perspectives on our current research in the area of Nonlinear Dynamics and Control. The seminar is particularly suitable for BSc and MSc students looking for a final project. Students, who want to obtain a Seminarschein, are welcome as well.

 

In physics, chemistry, biology, technology, and social sciences, one can find many examples of networks whose topologies evolve in time.

In adaptive networks, the dynamics on the nodes and the dynamics

of the links between the nodes are coupled to each other, producing emergent behavior that would not be seen in static network topologies. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. These include robust self-organization, formation of complex global topologies based on simple, local rules, plasticity as it occurs in learning processes in the brain, and the spontaneous emergence of hierarchical multicluster structures, in which an initially homogenous population of network nodes self-organizes into functionally distinct classes.

In the focus of the seminar will be recent studies of adaptive networks, we will discuss the wide field of their applications, analytical studies, complex dynamics, modeling and predicting state-topology coevolution.

 

Literature: www.itp.tu-berlin.de/schoell/nlds/seminare/

Schedule and Organization:

If you are interested in a particular topic, please contact one of the advisors. Final assignment of the topics will be done on 09.04.2019.

 

 

Schedule

Datum
Titel
Vortragender
Betreuer
09.04.

Introduction and organization

E. Schöll, A. Zakharova, I. Omelchenko
-
16.04
 
Flexibility of brain network modules

Narges Chinichian

ES
23.04.
 
Control of synchronization in power grids

Carl Totz

ES
30.04.
 
Adaptive oscillator networks with conserved overall coupling: Sequential firing and near-synchronized states [PIC11a]

07.05.
 
Controlling cluster synchronization by adapting the topology [LEH14]

14.05.
 
Emerging meso- and macroscales from synchronization of adap- tive networks [GUT11]

21.05.
 
Noise-enhanced coupling between two oscillators with long-term IO plasticity [LUE16]

IO
28.05.

Self-organized emergence of multi-layer structure and chi- mera states in dynamical networks with adaptive couplings [KAS17,KAS18a]
 

04.06.
Synchronization of chimera states in a multiplex system of phase oscillators with adaptive couplings [KAS18]
 

11.06.
 
Hierarchical transitions in multiplex adaptive networks of oscil- latory units [MAS18]

18.06
Inverse stochastic resonance in a system of excitable active IO rotators with adaptive coupling [BAC18a]
 

IO
25.06.
 
Itinerant chimeras in an adaptive network of pulse-coupled AZ oscillators [KAS19]




AZ
02.07.
Chimera states of neuron networks with adaptive coupling AZ [HUO19]

AZ
 

Wer Interesse an einem Vortrag hat, sollte sich mit den entsprechenden Betreuern in Verbindung setzen. Die Vortragsthemen werden dann spätestens in der ersten Seminarstunde am 09.04.2019 verteilt.

 

 

References

[POP13] O. Popovych, S. Yanchuk, and P. Tass, Self-organized noise resistance of oscillatory neural networks with spike timing-dependent plasticity. Sci. Rep. 3, 2926 (2013).

[PIC11a] C. B. Picallo and H. Riecke, Adaptive oscillator networks with conser- ved overall coupling: Sequential firing and near-synchronized states. Phys. Rev. E 83, 036206 (2011).

[LEH14] J. Lehnert, P. Hövel, A. A. Selivanov, A. L. Fradkov, and E. Schöll, Controlling cluster synchronization by adapting the topology. Phys. Rev. E 90, 042914 (2014).

[GUT11] R. Gutiérrez, A. Amann, S. Assenza, J. Gómez-Gardeñes, V. Latora, and S. Boccaletti, Emerging Meso- and Macroscales from Synchronization of Adaptive Networks. Phys. Rev. Lett. 107, 234103 (2011).

[LUE16] L. Lücken, O. Popovych, P. Tass, and S. Yanchuk, Noise-enhanced coupling between two oscillators with long-term plasticity. Phys. Rev. E 93, 032210 (2016).

[KAS17] D. V. Kasatkin, S. Yanchuk, E. Schöll, and V. I. Nekorkin, Self- organized emergence of multi-layer structure and chimera states in dynamical networks with adaptive couplings. Phys. Rev. E 96, 062211 (2017).

[KAS18a] D. V. Kasatkin and V. I. Nekorkin, The effect of topology on organi- zation of synchronous behavior in dynamical networks with adaptive couplings. Eur. Phys. J. Spec. Top. 227, 1051 (2018).

[KAS18] D. V. Kasatkin and V. I. Nekorkin, Synchronization of chimera states in a multiplex system of phase oscillators with adaptive couplings. Chaos 28, 1054 (2018).

[MAS18] O. V. Maslennikov and V. I. Nekorkin, Hierarchical transitions in multiplex adaptive networks of oscillatory units. Chaos 28, 121101 (2018).

[BAC18a] I. Bacic, V. Klinshov, V. Nekorkin, M. Perc, and I. Franović, Inverse stochastic resonance in a system of excitable active rotators with adaptive coupling. EPL 124, 40004 (2018).

[KAS19] D. V. Kasatkin, V. Klinshov, and V. I. Nekorkin, Itinerant chimeras in an adaptive network of pulse-coupled oscillators. Phys. Rev. E 99, 022203 (2019).

[HUO19] S. Huo, C. Tian, L. Kang, and Z. Liu, Chimera states of neuron networks with adaptive coupling. Nonlinear Dynamics (2019).

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