Complex networks are composed of a large number of highly interconnected dynamical units and, therefore, exhibit very complicate dynamics. Examples of such complex networks include Internet that is a network of routers or domains, the World Wide Web (WWW) that is a network of websites, the brain that is a network of neurons, and an organization that is a network of people. Since the introduction of the small-world network principle, a great deal of research has been focused on the dependence of the asymptotic behavior of interconnected oscillatory agents on the structural properties of complex networks. It has been found out that the general structure of the interaction network may play a crucial role in the emergence of synchronization phenomena in various fields such as physics, technology, and the life sciences.

Complex networks have already become an ideal research area for control engineer, mathematicians, computer scientists, and biologists to manage, analyze, and interpret functional information from real-world networks. Sophisticated computer system theories and computing algorithms have been exploited or emerged in the general area of computer mathematics, such as analysis of algorithms, artificial intelligence, automata, computational complexity, computer security, concurrency and parallelism, data structures, knowledge discovery, DNA and quantum computing, randomization, semantics, symbol manipulation, numerical analysis, and mathematical software. This special issue aims to bring together the latest approaches to understanding complex networks from a dynamic system perspective. Potential topics include, but are not limited to:

• Synchronization and control
• Topology structure and dynamics
• Stability analysis
• Robustness and fragility
• Applications in real-world complex networks
• Multiscale analysis

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