@article {CxContinuous2016,
	title = {Measuring the Complexity of Continuous Distributions},
	journal = {Entropy},
	volume = {18},
	number = {3},
	year = {2016},
	pages = {72},
	abstract = {We extend previously proposed measures of complexity, emergence, and self-organization to continuous distributions using differential entropy. Given that the measures were based on Shannon{\textquoteright}s information, the novel continuous complexity measures describe how a system{\textquoteright}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.},
	issn = {1099-4300},
	doi = {10.3390/e18030072},
	url = {http://www.mdpi.com/1099-4300/18/3/72},
	author = {Santamar{\'\i}a-Bonfil, Guillermo and Fern{\'a}ndez, Nelson and Gershenson, Carlos}
}
@inbook {Fernandez_Gershenson_2014,
	title = {Measuring Complexity in an Aquatic Ecosystem},
	booktitle = {Advances in Computational Biology},
	series = {Advances in Intelligent Systems and Computing},
	volume = {232},
	year = {2014},
	pages = {83-89},
	publisher = {Springer},
	organization = {Springer},
	abstract = {We 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.},
	doi = {10.1007/978-3-319-01568-2_12},
	url = {http://arxiv.org/abs/1305.5413},
	author = {Fern{\'a}ndez, Nelson and Gershenson, Carlos},
	editor = {Castillo, Luis F. and Cristancho, Marco and Isaza, Gustavo and Pinz{\'o}n, Andr{\'e}s and Corchado Rodr{\'\i}guez, Juan Manuel}
}
