观测窗中多元非线性时间序列的分析

从观察的角度去了解原有系统的特性，不同程度上会受到观测手段的限制．针对一个观测窗口获得的多元时间序列，利用一种能够更好地体现多元时间序列复杂的时空结构的多元奇异系统分析方法，研究多元序列的相关维数和最大李雅普诺夫指数的变化．利用多层感知器神经网络模型分析其可预测性．研究发现，随着观测窗中多元时间序列的变量数目的增加，反映出的复杂性有所提高，稳定性会产生波动，且相应的可预测性也会产生一些差异． 关键词：

ANALYSIS OF THE MULTIVARIATE TIME SERIES-IN AN OBSERVATION WINDOW

Generally,dynamical analyses of the original systems are limited to some extent by the observational methods.In this paper,by using the method of multivariate singular systems analysis (M SSA),which combines simultaneously information sampling the complete range of the spatial cross correlation function in signals with complex spatio temporal structure,we study the changes of the correlation dimensions and the largest Lyapunov exponents of the multivariate time series in an- observation window.And the characterization of prediction is discussed also with the multi-layer- perceptron.It is shown that when the number of the variates is increased,the complexity is also-- increased and the stability and the characterization of prediction are different.