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第928行： − + − − Nonlinear analysis is often necessary when the data is recorded from a [[nonlinear system]]. Nonlinear systems can exhibit complex dynamic effects including [[bifurcation theory|bifurcations]], [[chaos theory|chaos]], [[harmonics]] and [[subharmonics]] that cannot be analyzed using simple linear methods. Nonlinear data analysis is closely related to [[nonlinear system identification]].<ref name="SAB1">Billings S.A. "Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains". Wiley, 2013</ref> + − + − − '''<font color='#ff8000'></font>'''
→Nonlinear analysis非线性分析
*** '''<font color='#ff8000'>箱图Box plots</font>'''
*** '''<font color='#ff8000'>箱图Box plots</font>'''
====Nonlinear analysis非线性分析====
====非线性分析====
Nonlinear analysis is often necessary when the data is recorded from a [[nonlinear system]]. Nonlinear systems can exhibit complex dynamic effects including [[bifurcation theory|bifurcations]], [[chaos theory|chaos]], [[harmonics]] and [[subharmonics]] that cannot be analyzed using simple linear methods. Nonlinear data analysis is closely related to [[nonlinear system identification]].
Nonlinear analysis is often necessary when the data is recorded from a nonlinear system. Nonlinear systems can exhibit complex dynamic effects including bifurcations, chaos, harmonics and subharmonics that cannot be analyzed using simple linear methods. Nonlinear data analysis is closely related to nonlinear system identification.
Nonlinear analysis is often necessary when the data is recorded from a nonlinear system. Nonlinear systems can exhibit complex dynamic effects including bifurcations, chaos, harmonics and subharmonics that cannot be analyzed using simple linear methods. Nonlinear data analysis is closely related to nonlinear system identification.
'''<font color='#ff8000'>非线性分析Nonlinear analysis</font>'''通常在数据是从非线性系统中获取的时候是必要的。非线性系统可以表现出复杂的动力学效应，包括'''<font color='#ff8000'>分岔bifurcations</font>'''、'''<font color='#ff8000'>混沌chaos</font>'''、'''<font color='#ff8000'>谐波harmonics</font>'''和'''<font color='#ff8000'>次谐波subharmonics</font>'''，这些效应不能用简单的线性方法进行分析。非线性数据分析与非线性系统辨识密切相关。
'''非线性分析Nonlinear analysis'''通常是必要的，当数据是从非线性系统中获取的时候。非线性系统可以表现出复杂的动力学效应，包括'''分岔bifurcations'''、'''[[混沌]] chaos'''、'''谐波harmonics'''和'''<font color='#ff8000'>次谐波subharmonics</font>'''，这些效应不能用简单的线性方法进行分析。非线性数据分析与非线性系统辨识密切相关。<ref name="SAB1">Billings S.A. "Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains". Wiley, 2013</ref>
===Main data analysis 主要数据分析===
===Main data analysis 主要数据分析===