
ArchivIA  Archivio istituzionale dell'Universita' di Catania >
Tesi >
Tesi di dottorato >
Area 09  Ingegneria industriale e dell'informazione >
Utilizza questo identificativo per citare o creare un link a questo documento:
http://hdl.handle.net/10761/1481

Data:  17gen2014 
Autori:  Gambuzza, Lucia Valentina 
Titolo:  Memristors and networks: new structures for complexity 
Abstract:  One of the most interesting aspects of complexity is that it occurs at
different levels. It may occur at the level of interactions among the
agents that compose a complex network: despite the relatively simple
behavior of each single unit, the whole network may exhibit holistic
collective dynamics, such selforganization, synchronization, robustness
to failure, and so on; and it may occur, in the form of an aperiodic
irregular behavior, at the level of a system described by a loworder set
of ordinary differential equations, three, for instance, in the case of
continuoustime systems. This thesis focuses on both levels of complexity.
The first part, in particular, deals with complexity at the level of a
single dynamical system. The main contributions of the work summarized in
this thesis refer to the use of a new electronic component for the design
of chaotic circuits. This new component, the memristor, is at the same
time a memory element and a nonlinear element and for this reason has been regarded in literature as an effective block to reduce the minimum number of components needed to build a chaotic circuit. The original aspect of this thesis is the focus on a realistic model of memristor, that is a
model derived starting from the analysis of the real memristor device
discovered in the HP laboratories. The use of such approach introduces
constraints in the design that are not considered in idealized models such
as piecewise linear ones. The main results were: i) the introduction of a
configuration of two memristors in antiparallel which has been used as the
fundamental block to design a gallery of autonomous and nonautonomous
nonlinear circuits exhibiting a rich dynamics, including chaos; ii) the
design of a hybrid circuit which takes from the characterization
methodology of real memristors the idea of using a simple digital linear
control circuitry which allows chaos to be observed with the driving of a
single memristor.
The second part of the thesis focuses on synchronization on complex
networks. In particular, the onset of a new form of synchronization, named
remote synchronization, in complex networks has been investigated. Remote synchronization appears in starlike networks of coupled StuartLandau oscillators, where the hub node is characterized by an oscillation
frequency different from that of the leaves, as a regime in which the
peripheral nodes are synchronized each other but not with the hub. In this
thesis we have investigated if similar conditions can be observed in more
general frameworks. We have found that networks of not homogeneous nodes may display many pairs of nodes that, despite the fact that are not
directly connected nor connected through chains of synchronized nodes, are phase synchronized.
We have introduced measures to characterize this phenomenon and found that it is common both in scalefree and ErdosRenyi networks. Furthermore, this is an important mechanism to form clusters of
synchronized nodes in a network. Finally, we have linked the
appearance of pairs of remotely synchronized nodes to a topological
condition of inhibition of direct paths or paths through chains of
synchronized nodes, thus elucidating a mechanism which has lead to the
definition of a series of topologies where remote synchronization is
found.
Finally, we have explored the use of memristor as a synapse for complex
networks. Also in this case, we have used a configuration of two HP
memristors and shown that such configuration provides an adaptation rule
for the links of a complex network, enabling the emergence of a set of
weights leading to synchronization. 
In  Area 09  Ingegneria industriale e dell'informazione

Full text:
File 
Descrizione 
Dimensioni  Formato  Consultabilità 
GMBLVL83L44D960ZPhD_thesis_Gambuzza.pdf  MEMRISTORS AND NETWORKS: NEW STRUCTURES FOR COMPLEXITY  18,97 MB  Adobe PDF  Visualizza/apri


Tutti i documenti archiviati in ArchivIA sono protetti da copyright. Tutti i diritti riservati.
