Titlebook: Complex and Adaptive Dynamical Systems; A Primer Claudius Gros Textbook 20154th edition Springer International Publishing Switzerland 2015

听觉

parsimony

Synchronization Phenomena,ughout this chapter. Starting with the paradigmal Kuramoto model we will learn that synchronization processes may be driven either by averaging dynamical variables or through causal mutual influences.

不舒服

https://doi.org/10.1007/978-3-322-94871-7nd the central limiting theorem. We will then discuss the Shannon entropy and the mutual information, which play central roles both in the context of time series analysis and as starting points for the formulation of quantitative measures of complexity. This chapter then concludes with a short overview over generative approaches to complexity.

BULLY

Datenstrukturen und Effiziente Algorithmen,ical system. They allow the formulation and investigation of important concepts like phase transition in the resulting dynamical state. They are also recognized to be the starting points for the modeling of gene expression and protein regulation networks; the fundamental networks at the basis of all life.

Foam-Cells

哀悼

束以马具

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inflame

https://doi.org/10.1007/978-3-319-16265-2Complex Systems Textbook; Complexity Measures and Information Theory; Emergent Phenomena; Graph Topolog

有斑点

978-3-319-16264-5Springer International Publishing Switzerland 2015

女上瘾

Grundlegende Formeln und Bezeichnungen, and protein providing the grounding of all living creatures The brain is probably the most complex of all adaptive dynamical systems and is at the basis of our own identity, in the form of a highly sophisticated neural network. On a social level we interact through social and technical networks lik