基于噪声辨识系统状态的符号混沌特征

The Symbol-chaos Characteristics Based on Noise to Identify System Condition

动力系统含噪原因甚多,由于人类认识自然的能力有限,系统含噪几乎不可避免.当系统存在随机谐振或阈上随机谐振,或者系统具有非线性属性时,噪声常常有助于信号的传输或处理.故可考虑利用系统含噪程度的差异对系统进行状态辨识.由时间序列获得符号序列并得到其符号时间序列直方图后,可分别对直方图幅值计算混沌参数和符号参数,是为时间序列的符号混沌特征.有鉴于此,将复杂系统输出的时间序列变换为符号序列后进行符号分析和混沌分析,可形成一种带噪辨识复杂系统状态的新方法.

There are a lot of matters causing to dynamical system containing noise. It is hardy toly avoid noise to disturb a system because it is limited to understand nature by human being. While there is stochastic resonance or suprathreshold stochastic resonance in the system, or there is nonline property in the system, it often helps to transmit or process the signal based on the noise. So it could be considered to identify the system conadition utilizing the difference of system noise. The parameters of chaos and symbol, which are the symbol-chaos characteristics of time series, could be calculated by the histogram obtained with the symbolic series from a time series. Hereby a new measure on identifying the condition of complex system with noise could be offered by carrying out the symbolic and chaositc analysis for a symbolic series transformed from a time series exported from a complex system.