Constructing compact causal mathematical models for complex dynamics

From microbial communities, human physiology to social and biological/neural networks, complex interdependent systems display multi-scale spatio-temporal patterns that are frequently classified as non-linear, non-Gaussian, non-ergodic, and/or fractal. Distinguishing between the sources of nonlineari...

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Vydáno v:	2017 ACM IEEE 8th International Conference on Cyber Physical Systems (ICCPS) s. 97 - 107
Hlavní autoři:	Xue, Yuankun, Bogdan, Paul
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	New York, NY, USA ACM 18.04.2017
Edice:	ACM Other Conferences
Témata:	Biological system modeling Causal inference Complex dynamics Complex systems Computational modeling Computer systems organization > Embedded and cyber-physical systems Computing methodologies > Modeling and simulation > Model development and analysis > Modeling methodologies Fractal dynamics Fractals Mathematical model Mathematics of computing > Information theory Mathematics of computing > Probability and statistics > Multivariate statistics Mathematics of computing > Probability and statistics > Probabilistic inference problems Mathematics of computing > Probability and statistics > Stochastic processes Non-linearity Nonlinear dynamical systems Spatio-temporal coupling Theory of computation > Theory and algorithms for application domains > Machine learning theory > Models of learning Time series analysis causal inference fractal dynamics spatio-temporal coupling non-linearity complex dynamics
ISBN:	9781450349659, 145034965X
On-line přístup:	Získat plný text
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