Michael Small focuses on Complex network, Series, Algorithm, Dynamical systems theory and Time series. His Complex network research incorporates elements of Node, Theoretical computer science, Statistical physics and Cluster analysis. His Series study combines topics from a wide range of disciplines, such as Chaotic, Chaos theory, Probability and statistics, Embedding and Noise.
His research integrates issues of Attractor and Topology in his study of Chaotic. His Algorithm research is multidisciplinary, relying on both Term, Stochastic process, Statistics and Nonlinear system. His Dynamical systems theory research also works with subjects such as
Michael Small mainly focuses on Complex network, Algorithm, Series, Nonlinear system and Statistical physics. The various areas that Michael Small examines in his Complex network study include Node, Dynamical systems theory, Theoretical computer science and Topology. His research in Algorithm intersects with topics in Measure, Null hypothesis and Noise.
He combines subjects such as Embedding, Chaotic and Time series with his study of Series. His work carried out in the field of Chaotic brings together such families of science as Attractor and Control theory. As a part of the same scientific family, he mostly works in the field of Statistical physics, focusing on Artificial intelligence and, on occasion, Pattern recognition.
His primary scientific interests are in Complex network, Reservoir computing, Algorithm, Theoretical computer science and Nonlinear system. His Complex network study integrates concerns from other disciplines, such as Mechanism, Bifurcation, Tree and Function, Topology. His Algorithm research includes elements of Embedding, Markov process and Permutation.
His work deals with themes such as Statistical physics and Information Criteria, which intersect with Nonlinear system. Series and Markov model are commonly linked in his work. His Signal study deals with Chaotic intersecting with Attractor.
His primary areas of study are Complex network, Synchronization, Multivariate statistics, Algorithm and Measure. His Complex network research includes themes of Theoretical computer science, Tree, Focus, Data science and Mechanism. Michael Small has researched Synchronization in several fields, including Chaotic systems, Synchronism, Scalar and Control theory.
His Algorithm study incorporates themes from Embedding, Topological conjugacy and Markov process, Markov model. The study incorporates disciplines such as Chaotic, Attractor, Ergodicity, Transformation and Series in addition to Dynamical system. In his study, Time series is strongly linked to Statistical physics, which falls under the umbrella field of Ergodicity.
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Complex network from pseudoperiodic time series: Topology versus Dynamics
J. Zhang;Michael Small.
Physical Review Letters (2006)
Applied Nonlinear Time Series Analysis: Applications in Physics, Physiology and Finance
Superfamily phenomena and motifs of networks induced from time series
Xiaoke Xu;Jie Zhang;Michael Small.
Proceedings of the National Academy of Sciences of the United States of America (2008)
RECURRENCE-BASED TIME SERIES ANALYSIS BY MEANS OF COMPLEX NETWORK METHODS
Reik V. Donner;Michael Small;Jonathan F. Donges;Jonathan F. Donges;Norbert Marwan.
International Journal of Bifurcation and Chaos (2011)
Epidemic dynamics on scale-free networks with piecewise linear infectivity and immunization.
Xinchu Fu;Michael Small;David M. Walker;Haifeng Zhang.
Physical Review E (2008)
Complex network analysis of time series
Zhong Ke Gao;Michael Small;Jürgen Kurths;Jürgen Kurths;Jürgen Kurths.
Surrogate Test for Pseudoperiodic Time Series Data
Michael Small;Michael Small;Dejin Yu;Robert G. Harrison.
Physical Review Letters (2001)
Characterizing pseudoperiodic time series through the complex network approach
Jie Zhang;Junfeng Sun;Xiaodong Luo;Kai Zhang.
Physica D: Nonlinear Phenomena (2008)
The impact of awareness on epidemic spreading in networks
Qingchu Wu;Xinchu Fu;Michael Small;Xin-Jian Xu.
Hub nodes inhibit the outbreak of epidemic under voluntary vaccination
Haifeng Zhang;Haifeng Zhang;Haifeng Zhang;Jie Zhang;Changsong Zhou;Michael Small.
New Journal of Physics (2010)
Profile was last updated on December 6th, 2021.
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