基于神经网络的混沌时序数据失真检测方法研究

Study on Distortion Detective Method for Chaotic Time Series Based on Neural Network

介绍了时序数据的混沌识别方法,并根据混沌时序数据的可预测性,提出了一种基于神经网络的混沌时序数据失真检测方法.通过实例证明该方法能准确地检测出混沌时序数据的失真点,并将其还原.该方法既是检测过程同时也是修复的过程,在数据处理领域有一定的应用前景.

The method of chaos identifying for time series is introduced. By virtue of the predictability of chaotic time series, the distortion detective method for chaotic time series based on neural network is presented. The practical example demonstrate that the distortion data of chaotic time series can be detected and recovered correctly by this kind of method. The method is not only a detective process but also a recovering process, and the application prospect in the field of data processing is optimistic.