The complex systems approach offers an opportunity to replace the extant pre-dominant mechanistic view on sport-related phenomena.The emphasis on the environment-system relationship,the applications of complexity prin...The complex systems approach offers an opportunity to replace the extant pre-dominant mechanistic view on sport-related phenomena.The emphasis on the environment-system relationship,the applications of complexity principles,and the use of nonlinear dynamics mathematical tools propose a deep change in sport science.Coordination dynamics,ecological dynamics,and network approaches have been successfully applied to the study of different sport-related behaviors,from movement patterns that emerge at different scales constrained by specific sport contexts to game dynamics.Sport benefit from the use of such approaches in the understanding of technical,tactical,or physical conditioning aspects which change their meaning and dilute their frontiers.The creation of new learning and training strategies for teams and individual athletes is a main practical consequence.Some challenges for the future are investigating the influence of key control parameters in the nonlinear behavior of athlete-environment systems and the possible relatedness of the dynamics and constraints acting at different spatio-temporal scales in team sports.Modelling sport-related phenomena can make useful contributions to a better understanding of complex systems and vice-versa.展开更多
In this paper, it is proved that the correlation dimension estimate of a nonlinear dynamical system with its multivariate observation series is the same as that with its univariate observation series. Based on this re...In this paper, it is proved that the correlation dimension estimate of a nonlinear dynamical system with its multivariate observation series is the same as that with its univariate observation series. Based on this result, an inference method is presented, and the Nonlinear Dependence Coefficient is defined. This method is designed for testing nonlinear dependence between time series, and can be used in economic analysis and forecasting. Numerical results show the method is effective.展开更多
文摘The complex systems approach offers an opportunity to replace the extant pre-dominant mechanistic view on sport-related phenomena.The emphasis on the environment-system relationship,the applications of complexity principles,and the use of nonlinear dynamics mathematical tools propose a deep change in sport science.Coordination dynamics,ecological dynamics,and network approaches have been successfully applied to the study of different sport-related behaviors,from movement patterns that emerge at different scales constrained by specific sport contexts to game dynamics.Sport benefit from the use of such approaches in the understanding of technical,tactical,or physical conditioning aspects which change their meaning and dilute their frontiers.The creation of new learning and training strategies for teams and individual athletes is a main practical consequence.Some challenges for the future are investigating the influence of key control parameters in the nonlinear behavior of athlete-environment systems and the possible relatedness of the dynamics and constraints acting at different spatio-temporal scales in team sports.Modelling sport-related phenomena can make useful contributions to a better understanding of complex systems and vice-versa.
文摘In this paper, it is proved that the correlation dimension estimate of a nonlinear dynamical system with its multivariate observation series is the same as that with its univariate observation series. Based on this result, an inference method is presented, and the Nonlinear Dependence Coefficient is defined. This method is designed for testing nonlinear dependence between time series, and can be used in economic analysis and forecasting. Numerical results show the method is effective.
