About Network Structures and Systems Complexity

TL;DR

This paper analyzes complex network systems by introducing flow adjacency matrices, defining dynamic characteristics, and proposing methods for identifying real structures and reducing model dimensionality.

Contribution

It introduces the flow core concept and methods for structural identification and dimensionality reduction in complex network systems.

Findings

Flow core has advantages over k-core.

Methods for real structure identification are proposed.

Dimensionality reduction techniques are developed.

Abstract

This paper provides the analysis for structural and functional approaches of complex network systems research. In order to study the behavior of these systems the flow adjacency matrices were introduced, and local and global dynamic characteristics of system elements were defined. The notion of the flow core of network system was introduced and its advantages over the k-core of complex network were analyzed. The methods were proposed for identifying real structure of network system and reducing the dimensionality of its model.