混沌相空间重构参数的选取与仿真

Study on Parameters Selection in Chaotic Phase Reconstruction

对混沌时间序列进行相空间重构时,提出采用互信息量法确定延迟时间、用神经网络法确定嵌入维数的新算法。经验证该方法能够确定相空间重构的延迟时间和最佳嵌入维数,并且能够从时间序列中成功地重构原系统的相空间。

Making use of the mutual information function to determine the delay time and the neural network method to determine the optimal embedding dimension was proposed, experience has proved that this method can determine the delay time and optimal embedding dimension and can recover the original phase space from the time series successfully.