
doi: 10.1109/dsc.2016.71
Exploring the topological structures of networks by mathematical methods is powerful and efficient in researching real networks. There are many successful mathematical methods shown in scale-free networks that are forming branches of mathematics and network science. We are motivated from the cumulative degree distribution and edge-cumulative degree distribution of scale-free networks, and discover several newly mixed cumulative distributions for scale-free networks. By three classical scale-free networks we compute our mixed cumulative distributions, we, also, discover some phenomenons between known and new cumulative distributions. Some problems are presented for further investigate scale-free networks.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
