888 resultados para non-smooth dynamical systems


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In recent decades, concepts and ideas from James J. Gibson’s theory of direct perception in ecological psychology have been applied to the study of how perception and action regulate sport performance. This article examines the influence of different streams of thought in ecological psychology for studying cognition and action in the diverse behavioural contexts of sport and exercise. In discussing the origins of ecological psychology it can be concluded that psychologists such as Lewin, and to some extent Heider, provided the initial impetus for the development of key ideas. We argue that the papers in this special issue clarify that the different schools of thinking in ecological psychology have much to contribute to theoretical and practical developments in sport and exercise psychology. For example, Gibson emphasized and formalized how the individual is coupled with the environment; Brunswik raised the issue of the ontology of probability in human behaviour and the problem of representative design for experimental task constraints; Barker looked carefully into extra-individual behavioural contexts and Bronfenbrenner presented insights pertinent to the relations between behaviour contexts, and macro influences on behaviour. In this overview, we highlight essential issues from the main schools of thought of relevance to the contexts of sport and exercise, and we consider some potential theoretical linkages with dynamical systems theory.

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In sport and exercise biomechanics, forward dynamics analyses or simulations have frequently been used in attempts to establish optimal techniques for performance of a wide range of motor activities. However, the accuracy and validity of these simulations is largely dependent on the complexity of the mathematical model used to represent the neuromusculoskeletal system. It could be argued that complex mathematical models are superior to simple mathematical models as they enable basic mechanical insights to be made and individual-specific optimal movement solutions to be identified. Contrary to some claims in the literature, however, we suggest that it is currently not possible to identify the complete optimal solution for a given motor activity. For a complete optimization of human motion, dynamical systems theory implies that mathematical models must incorporate a much wider range of organismic, environmental and task constraints. These ideas encapsulate why sports medicine specialists need to adopt more individualized clinical assessment procedures in interpreting why performers' movement patterns may differ.

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The aims of this chapter are twofold. First, we show how experiments related to nonlinear dynamical systems theory can bring about insights on the interconnectedness of different information sources for action. These include the amount of information as emphasised in conventional models of cognition and action in sport and the nature of perceptual information typically emphasised in the ecological approach. The second aim was to show how, through examining the interconnectedness of these information sources, one can study the emergence of novel tactical solutions in sport; and design experiments where tactical/decisional creativity can be observed. Within this approach it is proposed that perceptual and affective information can be manipulated during practice so that the athlete's cognitive and action systems can be transposed to a meta-stable dynamical performance region where the creation of novel action information may reside.

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The purpose of this paper is threefold. First, we propose a systemic view of communication based in autopoiesis, the theory of living systems formulated by Maturana & Varela (1980, 1987). Second, we show the links between the underpinning assumptions of autopoiesis and the sociolinguistic approaches of Halliday (1978), Fairclough (1989, 1992, 1995) and Lemke (1995, 1994). Third, we propose a theoretical and analytical synthesis of autopoiesis and sociolinguistics for the study of organisational communication. In proposing a systemic theory for organisational communication, we argue that traditional approaches to communication, information, and the role of language in human organisations have, to date, been placed in teleological constraints because of an inverted focus on organisational purpose-the generally perceived role of an organisation within society-that obscure, rather than clarify, the role of language within human organisations. We argue that human social systems are, according to the criteria defined by Maturana and Varela, third-order, non-organismic living systems constituted in language. We further propose that sociolinguistics provides an appropriate analytical tool which is both compatible and penetrating in synthesis with the systemic framework provided by an autopoietic understanding of social organisation.

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In this paper, A Riesz fractional diffusion equation with a nonlinear source term (RFDE-NST) is considered. This equation is commonly used to model the growth and spreading of biological species. According to the equivalent of the Riemann-Liouville(R-L) and Gr¨unwald-Letnikov(GL) fractional derivative definitions, an implicit difference approximation (IFDA) for the RFDE-NST is derived. We prove the IFDA is unconditionally stable and convergent. In order to evaluate the efficiency of the IFDA, a comparison with a fractional method of lines (FMOL) is used. Finally, two numerical examples are presented to show that the numerical results are in good agreement with our theoretical analysis.

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In this paper, we consider a time-space fractional diffusion equation of distributed order (TSFDEDO). The TSFDEDO is obtained from the standard advection-dispersion equation by replacing the first-order time derivative by the Caputo fractional derivative of order α∈(0,1], the first-order and second-order space derivatives by the Riesz fractional derivatives of orders β 1∈(0,1) and β 2∈(1,2], respectively. We derive the fundamental solution for the TSFDEDO with an initial condition (TSFDEDO-IC). The fundamental solution can be interpreted as a spatial probability density function evolving in time. We also investigate a discrete random walk model based on an explicit finite difference approximation for the TSFDEDO-IC.