2019/05/13 by Felipe S. Abrahão, Abrahão, Felipe S., Klaus Wehmuth +3
Physics and Astronomy · Computer Science · #Advanced Thermodynamics and Statistical Mechanics #Complex Network Analysis Techniques #Neural Networks Stability and Synchronization
paper · pdf · doi:10.48550/arxiv.1905.05276
This work presents some outcomes of a theoretical investigation of incompressible high-order networks defined by a generalized graph representation. We study some of their network topological properties and how these may be related to real-world complex networks. We show that these networks have very short diameter, high k-connectivity, degrees of the order of half of the network size within a strong-asymptotically dominated standard deviation, and rigidity with respect to automorphisms. In addition, we demonstrate that incompressible dynamic (or dynamic multilayered) networks have transtemporal (or crosslayer) edges and, thus, a snapshot-like representation of dynamic networks is inaccurate for capturing the presence of such edges that compose underlying structures of some real-world networks.