Lossy Asymptotic Equipartition property for Networked Data Structures

TL;DR

This paper establishes a generalized asymptotic equipartition property for networked data modeled as colored random graphs, using large deviation principles, with applications demonstrated in biology.

Contribution

It introduces a new generalized AEP for colored random graphs, extending classical information theory to networked data structures.

Findings

Proves a generalized AEP for colored random graphs

Uses large deviation principles for empirical measures

Applies results to a biological example

Abstract

In this article we prove a Generalized Asypmtotic Equipartition Property for Networked Data Structures modelled as coloured random graphs. The main techniques in this article remains large deviation principles for suitably defined empirical measures on coloured random graphs. We apply our main result to a concrete example from the field of Biology.