Applications of Nonlinear Methods to Signal Detection of Time Series

The analysis of time series from real system is the most direct link between nonlinear theory and real world. If the measure data from nonlinear system are described linearly, useful signal could not found out. The nonlinear methods in this paper, Poincaré map, fractal dimension, and correlation dimension, are introduced to detect chaos phenomena in a system. These nonlinear algorithms can be used to pick up signal characteristics of time series. Some examples are presented to illustrate how to apply these methods in signal detection and engineering signal analysis.