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Cellular automata (CA) represent an interesting approach to the modelling of dynamical systems evolving on the basis of local interactions and internal transformations.
Fractional calculus (differentiation and integration of arbitrary order) is proved to be an important tool in the modelling of dynamical systems associated with phenomena such as fractal and chaos.
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Finally, via applications to several models of dynamical networks and human brain images, we demonstrate how information dynamics relates the structure of complex networks to their function, and how it can invert such analysis to infer structure from dynamics.
Horska, J. "Comparison of sensitivity properties of selected models of dynamical systems," Radioengineering, vol.9, no.3, pp.17-21.
Buehler, M. J., van Duin, A. C. T. & Goddard, W. A. Multiparadigm modeling of dynamical crack propagation in silicon using a reactive force field.
System identification concerns the construction and validation of mathematical models of dynamical systems from experimental data.
In almost all fields of mechanical engineering, the mathematical models of dynamical systems become more and more computationally expensive.
The paper presents a general approach to fault detection and isolation based on symbolic models of dynamical systems.
A novel procedure is developed for the identification of linear discrete models of dynamical systems from noisy data.
A stable adaptive neural-network-based control scheme for dynamical systems is presented and a continuous recurrent neural network model of dynamical systems is constructed in this paper.
The subsumption of the new theorems by the classical stability theorems serves as a model of dynamical subsumption, forming the basis of the design methodology.
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