SYNCHRONIZATION IN DYNAMICAL NETWORKS
SYNCHRONIZABILITY, NEURAL NETWORK MODELS AND EEG ANALYSIS
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Complex dynamical networks are ubiquitous in many fields of science from engineering to biology, physics, and sociology. Collective behavior, and in particular synchronization, is one of the most interesting consequences of interaction of dynamical systems over complex networks. Analyzing statistical and dynamical properties of complex networks may lead us to understand them deeper. This book discuses the problem of synchronizability in dynamical networks and gives some possible interpretations of that. Various methods for enhancing the synchronizability of dynamical networks through link weig...
Complex dynamical networks are ubiquitous in many
fields of science from engineering to biology,
physics, and sociology. Collective behavior, and in
particular synchronization, is one of the most
interesting consequences of interaction of dynamical
systems over complex networks. Analyzing statistical
and dynamical properties of complex networks may
lead us to understand them deeper. This book
discuses the problem of synchronizability in
dynamical networks and gives some possible
interpretations of that. Various methods for
enhancing the synchronizability of dynamical
networks through link weighting or rewiring is
addressed. The book also studies the synchronization
phenomenon in networks of model neurons and gives a
simple model for investigating the behavior of
interacting locally synchronized gamma oscillations.
In the last section of the book the
interdependencies within the time series obtained
through electroencephalography is studied. Proper
synchronization measures are introduced
electroencephalography-specific maps for patients
suffering from schizophrenia or Alzheimer s disease
are obtained.
fields of science from engineering to biology,
physics, and sociology. Collective behavior, and in
particular synchronization, is one of the most
interesting consequences of interaction of dynamical
systems over complex networks. Analyzing statistical
and dynamical properties of complex networks may
lead us to understand them deeper. This book
discuses the problem of synchronizability in
dynamical networks and gives some possible
interpretations of that. Various methods for
enhancing the synchronizability of dynamical
networks through link weighting or rewiring is
addressed. The book also studies the synchronization
phenomenon in networks of model neurons and gives a
simple model for investigating the behavior of
interacting locally synchronized gamma oscillations.
In the last section of the book the
interdependencies within the time series obtained
through electroencephalography is studied. Proper
synchronization measures are introduced
electroencephalography-specific maps for patients
suffering from schizophrenia or Alzheimer s disease
are obtained.
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