Cooperative processes in complex networks with imperfections

Examples of cooperative behavior in complex networks with inherent or created imperfections are in the focus of study in this thesis. The complex networks represent real world systems where a number of entities cooperate through their interconnections. All entities and their interactions have some unique characteristics that determine the overall dynamics of the system. Therefore, the main topic of the thesis is the study of some of the effects of the uniqueness of the individual entities on the dynamical behavior of real systems, the effects of the neglecting of some physical aspects during modeling and approaches of combining the distinct qualities of individual models of nonlinear systems in developing better representation of the system of interest. The analyses show that model imperfections should lead to appropriate adaptation of the learning procedures used for state and parameter estimation in modeling. Furthermore, approaches of interactively combining imperfect models can lead to improvements in nonlinear modeling of real world phenomena. The study of synchronization and consensus in complex networks revealed some of the effects of the uniqueness of entities and their interactions, which can alter the convergence rate or introduce some new interesting behaviors.