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A method for finding aggregated representations of linear dynamical systems

Olof Görnerup (Institutionen för energi och miljö, Fysisk resursteori) ; Martin Nilsson Jacobi (Institutionen för energi och miljö, Fysisk resursteori)
Advances in Complex Systems (0219-5259). Vol. 13 (2010), 2, p. 199-215.
[Artikel, refereegranskad vetenskaplig]

A central problem in the study of complex systems is to identify hierarchical and intertwined dynamics. A hierarchical level is defined as an aggregation of the system's variables such that the aggregation induces its own closed dynamics. In this paper, we present an algorithm that finds aggregations of linear dynamical systems, e. g. including Markov chains and diffusion processes on weighted and directed networks. The algorithm utilizes that a valid aggregation with n states correspond to a set of n eigenvectors of the dynamics matrix such that these respect the same permutation symmetry with n orbits. We exemplify the applicability of the algorithm by employing it to identify coarse grained representations of cellular automata.

Nyckelord: Hierarchical dynamics, aggregation of variables, lumpability, aggregated Markov chains, state space reduction, hierarchical networks, network clustering, cellular automata, weak lumpability, markov-chains, cellular-automata, prediction, complexity, reduction, variables, selection

Denna post skapades 2010-07-26. Senast ändrad 2016-08-18.
CPL Pubid: 123961


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Institutioner (Chalmers)

Institutionen för energi och miljö, Fysisk resursteori (2005-2017)



Chalmers infrastruktur