Effects of refractory period on the dynamical range in excitable networks are studied by computer simulations and theoretical analysis. The first effect is that the maximum or peak of the dynamical range appears when ...Effects of refractory period on the dynamical range in excitable networks are studied by computer simulations and theoretical analysis. The first effect is that the maximum or peak of the dynamical range appears when the largest eigenvalue of adjacent matrix is larger than one. We present a modification of the theory of the critical point by considering the correlation between excited nodes and their neighbors, which is brought by the refractory period. Our analysis provides the interpretation for the shift of the peak of the dynamical range. The effect is negligible when the average degree of the network is large. The second effect is that the dynamical range increases as the length of refractory period increases, and it is independent of the average degree. We present the mechanism of the second effect. As the refractory period increases,the saturated response decreases. This makes the bottom boundary of the dynamical range smaller and the dynamical range extend.展开更多
Focusing on common and significant forecast errorsthe zonal mean errors in the numerical prediction model, this report proposes an approach to improving the dynamical extended-range (monthly) prediction. Firstly, the ...Focusing on common and significant forecast errorsthe zonal mean errors in the numerical prediction model, this report proposes an approach to improving the dynamical extended-range (monthly) prediction. Firstly, the monthly pentad-mean nonlinear dynamical regional predic-tion model of the zonal-mean height based on a large num-ber of historical data is constituted by employing the recon-struction phase space theory and the spatio-temporal series predictive method. The zonal height thus produced is trans-formed to its counterpart in the numerical model and fur-ther used to revise the numerical model prediction during the integration process. In this way, the two different kinds of prediction are combined. The forecasting experimenal results show that the above hybrid approach not only re-duces the systematical error of the numerical model, but also improves the forecast of the non-axisymmetric components due to the wave-flow interaction.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.11675096)the Fundamental Research Funds for the Central Universities of China(Grant No.GK201702001)the Fund for the Academic Leaders and Academic Backbones,Shaanxi Normal University of China(Grant No.16QNGG007)
文摘Effects of refractory period on the dynamical range in excitable networks are studied by computer simulations and theoretical analysis. The first effect is that the maximum or peak of the dynamical range appears when the largest eigenvalue of adjacent matrix is larger than one. We present a modification of the theory of the critical point by considering the correlation between excited nodes and their neighbors, which is brought by the refractory period. Our analysis provides the interpretation for the shift of the peak of the dynamical range. The effect is negligible when the average degree of the network is large. The second effect is that the dynamical range increases as the length of refractory period increases, and it is independent of the average degree. We present the mechanism of the second effect. As the refractory period increases,the saturated response decreases. This makes the bottom boundary of the dynamical range smaller and the dynamical range extend.
基金supported by the National Key Project for Development of Science and Technology(Grant No.96-908-02)by the National Natural Science Foundation of China(Grant No.40175013)partly by the Project of Chinese Academy of Sciences(Grant No.ZKCX2-SW-210).
文摘Focusing on common and significant forecast errorsthe zonal mean errors in the numerical prediction model, this report proposes an approach to improving the dynamical extended-range (monthly) prediction. Firstly, the monthly pentad-mean nonlinear dynamical regional predic-tion model of the zonal-mean height based on a large num-ber of historical data is constituted by employing the recon-struction phase space theory and the spatio-temporal series predictive method. The zonal height thus produced is trans-formed to its counterpart in the numerical model and fur-ther used to revise the numerical model prediction during the integration process. In this way, the two different kinds of prediction are combined. The forecasting experimenal results show that the above hybrid approach not only re-duces the systematical error of the numerical model, but also improves the forecast of the non-axisymmetric components due to the wave-flow interaction.
