01125nas a2200157 4500008004100000022001400041245005700055210005700112300000700169490000700176520066200183100003400845700002300879700002300902856004200925 2016 eng d a1099-430000aMeasuring the Complexity of Continuous Distributions0 aMeasuring the Complexity of Continuous Distributions a720 v183 aWe extend previously proposed measures of complexity, emergence, and self-organization to continuous distributions using differential entropy. Given that the measures were based on Shannon's information, the novel continuous complexity measures describe how a system's predictability changes in terms of the probability distribution parameters. This allows us to calculate the complexity of phenomena for which distributions are known. We find that a broad range of common parameters found in Gaussian and scale-free distributions present high complexity values. We also explore the relationship between our measure of complexity and information adaptation.1 aSantamaría-Bonfil, Guillermo1 aFernández, Nelson1 aGershenson, Carlos uhttp://www.mdpi.com/1099-4300/18/3/7201387nas a2200205 4500008004100000245004900041210004900090260001300139300001000152490000800162520081200170100002300982700002301005700002301028700002201051700001901073700002101092700003301113856003501146 2014 eng d00aMeasuring Complexity in an Aquatic Ecosystem0 aMeasuring Complexity in an Aquatic Ecosystem bSpringer a83-890 v2323 aWe apply formal measures of emergence, self-organization, homeostasis, autopoiesis and complexity to an aquatic ecosystem; in particular to the physiochemical component of an Arctic lake. These measures are based on information theory. Variables with an homogeneous distribution have higher values of emergence, while variables with a more heterogeneous distribution have a higher self-organization. Variables with a high complexity reflect a balance between change (emergence) and regularity/order (self-organization). In addition, homeostasis values coincide with the variation of the winter and summer seasons. Autopoiesis values show a higher degree of independence of biological components over their environment. Our approach shows how the ecological dynamics can be described in terms of information.1 aFernández, Nelson1 aGershenson, Carlos1 aCastillo, Luis, F.1 aCristancho, Marco1 aIsaza, Gustavo1 aPinzón, Andrés1 aRodríguez, Juan, Manuel Cor uhttp://arxiv.org/abs/1305.5413