基于云变换的混沌动力系统逼近性研究

On approximation of chaotic dynamic system based on cloud transform

为了解决混沌系统内禀的强非线性和类随机性对由混沌时间序列重构混沌吸引子的不利影响,基于云模型理论,提出一种基于云变换的混沌动力学系统逼近方法;该方法将非线性时间序列看成是许多备选序列在某一概率意义下的实现,并对Lorenz混沌时间序列和NewtonLeipnik混沌时间序列在无噪和有噪两种情况下进行仿真,验证了该方法的可行性。

In order to address the intrinsic challenge of attractor reconstruction from the time series of a chaotic system,such as strong nonlinearity and random like properties,an approximation scheme was propsed based on cloud transformation,which is the natural result of cloud theory. The method is considered nonlinear time series as the implementation of a number of alternative sequences in the sense of a certain probability. Furthermore,the feasibility of the method was verified via the chaotic series reconstruction of Lorenz chaotic system and Newton-Leipnik chaotic system with and without externally added noises.