Details

Autor(en) / Beteiligte

• Ke, Da-guan

Titel

Unifying complexity and information

Ist Teil von

• Scientific reports, 2013-04, Vol.3 (1), p.1585-1585, Article 1585

Ort / Verlag

England: Nature Publishing Group

Erscheinungsjahr

2013

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Complex systems, arising in many contexts in the computer, life, social, and physical sciences, have not shared a generally-accepted complexity measure playing a fundamental role as the Shannon entropy H in statistical mechanics. Superficially-conflicting criteria of complexity measurement, i.e. complexity-randomness (C-R) relations, have given rise to a special measure intrinsically adaptable to more than one criterion. However, deep causes of the conflict and the adaptability are not much clear. Here I trace the root of each representative or adaptable measure to its particular universal data-generating or -regenerating model (UDGM or UDRM). A representative measure for deterministic dynamical systems is found as a counterpart of the H for random process, clearly redefining the boundary of different criteria. And a specific UDRM achieving the intrinsic adaptability enables a general information measure that ultimately solves all major disputes. This work encourages a single framework coving deterministic systems, statistical mechanics and real-world living organisms.