| Abstract: |
| Singular Spectrum Analysis (SSA) has been extensively used in the analysis of nonlinear dynamical systems obtained by experimental time series. SSA gives the estimates of the statistical dimensions of the dynamical system. SSA also explains the main physical phenomena reflected by the time series. It gives adaptive spectral filters associated with the dominant features of the nonlinear dynamical system to separate the noise characteristics of the data. In this study the application of SSA and its variants in the analysis of nonlinear dynamical chemical process systems is reviewed. |
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