Entropy | Special Issue : Information Theory in Complex Systems

Complexity Digest

Complex systems are ubiquitous in the natural and engineered worlds. Examples are self-assembling materials, the Earth’s climate, single- and multi-cellular organisms, the brain, and coupled socio-economic and socio-technical systems, to mention a few canonical examples. The use of Shannon information theory to study the behavior of such systems, and to explain and predict their dynamics, has gained significant attention, both from a theoretical and from an experimental viewpoint. There have been many advances in applying Shannon theory to complex systems, including correlation analyses for spatial and temporal data and construction and clustering techniques for complex networks. Progress has often been driven by the application areas, such as genetics, neurosciences, and the Earth sciences.

The application of Shannon theory to data of real-world complex systems are often hindered by the frequent lack of stationarity and sufficient statistics. Further progress on this front call for new statistical techniques based on Shannon information…

View original post 87 more words