|Support type:||Scholarships in Brazil - Post-Doctorate|
|Effective date (Start):||January 01, 2012|
|Effective date (End):||September 30, 2012|
|Field of knowledge:||Engineering - Electrical Engineering - Electrical, Magnetic and Electronic Circuits|
|Principal Investigator:||José Roberto Castilho Piqueira|
|Grantee:||Rosângela Follmann Bageston|
|Home Institution:||Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil|
Systems with mutual dynamic behavior are found in abundance in nature and technologies that surround us. As an example we can mention the fireflies flashing in unison, a flock of birds, robots performing joint tasks and also in applications such as reliable communication systems. This emergent behavior cannot be explained in terms of the individual dynamics of the network element. These collective behaviors are modeled dynamically involving a large number of elements (oscillators) interconnected by coupling interactions. As a result of this interaction we have the emergence of synchronization. This phenomenon reveals itself in several ways. In particular, when the coupled systems are not completely identical and the coupling strength is not so intense, we have the so-called phase synchronization. In this kind of synchronization the phase difference between the systems remains limited, while their amplitudes remain uncorrelated. Recently it was discovered that the phenomenon of phase synchronization is ubiquitous in nature, manifesting itself even in chaotic systems, with phase-coherent or noncoherent dynamics. The characterization of this phenomenon in large sets of interacting systems is an emerging problem that is found in neuroscience during cognitive process and in certain neurological disorders as Parkinson's disease. In this way, understanding the evolution of synchronization through topological structures and infer methodologies to characterize the phase synchronization in networks are relevant issues nowadays. The main goals of this project are: (1) develop mechanisms to identify clusters of phase synchronization in sets of coupled complex systems and (2) characterize optimal synchronous clusters, exploring and assessing the capability of information processing in these synchronous states.