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Encyclopedia > Dynamical systems theory

Dynamical systems theory is an area of mathematics used to describe the behavior of complex systems by employing differential equations.


Proponents of the dynamical systems theory approach to cognition (see dynamicism) believe that differential equations are the most appropriate tool for modeling human behavior. These equations are interpreted to represent an agent's cognitive trajectory through state space. In other words, dynamicists argue that psychology should be (or is) the description (via differential equations) of the cognitions and behaviors of an agent under certain environmental and internal pressures. The language of chaos theory is also frequently adopted.


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DYNAMICAL SYSTEMS THEORY: a Relevant Framework for Performance-Oriented Sports Biomechanics Research (3472 words)
Dynamical systems theorists claim that the number of biomechanical degrees of freedom of the motor system is dramatically reduced through the development of coordinative structures or temporary assemblages of muscle complexes (Turvey, 1990).
Dynamical systems theorists, on the other hand, argue that the existence of a common optimal motor pattern is a fallacy, owing to the intra- and inter-individual variability typically observed in human motor performance.
Dynamical systems theorists, however, suggest that movement variability is an intrinsic feature of skilled motor performance, as the variability provides the flexibility required to adapt to complex dynamic sport environments (Williams et al., 1999).
Dynamical Systems Theory (1482 words)
In dissipative systems, when the temporal evolution is bounded in a limited region of the phase space, a small volume should fold, after an initial stretching due to the strong sensitivity on the initial state.
In high dimensional systems besides the practical numerical difficulties one has to face with additional problems, for instance the spatial correlation, the existence of a thermodynamic limit for quantities as the whole spectrum of the Lyapunov exponents and the dimension of the attractor.
This is a rephrasing, in the context of the dynamical systems, of the theorem for the maximum compressibility which, in information theory, is stated in terms of the Shannon entropy.
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