The Research On Weighted Complex Network And Its Applications In Electronic Circuits

In the real world, many systems can be characterized by complex net-work models. Recently, the unweighted network models studied in many ex-isting literatures are simplified modeling of real networks, while weighted network models can provide more realistic and comprehensive descriptions of real networks. The research is emphasized on weighted networks that a new comprehensive weighted evolving network model which yields three power-law distributions of the node degrees, connection weights and node strengths is developed.Analyzing electronic circuit systems by the complex network theory is elementary both home and abroad in which the current method is unweighted network analysis. The weighted network analysis method used in this paper can be more effective, and the concept that the complex network theory can be used to guide printed circuit board wiring is put forward.Network weights may affect various properties and dynamics of network to a large extent, different weights might lead to distinct dynamics. The con-nection strengths are of great difference in some electronic circuits, so it can not describe the real circuits system well if considered that the strengths be-tween components are always one. Analog circuit, digital circuit and hybrid circuit of which we established complex network models and gained statisti-cal parameters are analyzed. Large complex network dedicated analysis soft-ware–Pajek by which we realized the analysis of analog circuit and digital circuit by unweighted network analysis method is applied. While the hybrid circuit analysis in this paper takes a weighted network analysis method which indicates more effective and reasonable than the unweighted one. PCB layout and routing algorithms are essential to printed circuit board design. At present, the algorithms in the application are not ideal, such as, the task of manual layout is heavy, for a bit more complex circuit, it will fail to route all the components. From the perspective of complex network, op-timized algorithms which take into account the weights and strengths of the components are provided.