Dynamics of Complex Autonomous Boolean Networks

by David P. Rosin
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David P. Rosin Dynamics of Complex Autonomous Boolean Networks
David P. Rosin - Dynamics of Complex Autonomous Boolean Networks

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This thesis focuses on the dynamics of autonomous Boolean networks, on the basis of Boolean logic functions in continuous time without external clocking. These networks are realized with integrated circuits on an electronic chip as a field programmable gate array (FPGA) with roughly 100,000 logic gates, offering an extremely flexible model system. It allows fast and cheap design cycles and large networks with arbitrary topologies and coupling delays.
The author presents pioneering results on theoretical modeling, experimental realization, and selected applications. In this regard, three classes of novel dynamic behavior are investigated: (i) Chaotic Boolean networks are proposed as high-speed physical random number generators with high bit rates. (ii) Networks of periodic Boolean oscillators are home to long-living transient chimera states, i.e., novel patterns of coexisting domains of spatially coherent (synchronized) and incoherent (desynchronized) dynamics. (iii) Excitable networks exhibit cluster synchronization and can be used as fast artificial Boolean neurons whose spiking patterns can be controlled. This work presents the first experimental platform for large complex networks, which will facilitate exciting future developments.


David P. Rosin

Further information

Illustrations Note:
79 schwarz-weiße und 9 farbige Abbildungen, Bibliographie

Nominated as an outstanding Ph.D. thesis by the Technical University of Berlin, Germany

Reports on important progress in the study of complex networks

Introduces applications in physical random number generation and neuro-inspired computing

Includes hardware code to experimentally realize large complex networks with asynchronous logic designs

Media Type:
Springer International Publishing
Biography Artist:
David Rosin studied physics at Technische Universität Berlin, Germany, and received his Bachelor Degree in 2009 and his Master Degree in 2011. He researched complex dynamical networks in the framework of a collaboration between Daniel J. Gauthier from Duke University (USA) and Eckehard Schöll from Technische Universität Berlin (Germany) from 2010 till 2014. This work was submitted as a Doctoral Thesis in physics at Technische Universität Berlin in 2014.
Number of Pages:

Master Data

Product Type:
Hardback book
Package Dimensions:
0.246 x 0.165 x 0.019 m; 0.472 kg
Manufacturer Part Number:
79 black & white illustrations
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