Fig. 1 | Journal of Nonlinear Science

Fig. 1

From: Memory-Based Reduced Modelling and Data-Based Estimation of Opinion Spreading

Fig. 1

Relation between different system identification methods. All of them are based on solving a least squares problem with respect to transformations of past to future states. While the AR minimization problem can be seen as the DMD problem on delay-embedded states and SINDy finds a nonlinear instead of linear connection between states (as in Hankel-DMD in Arbabi and Mezic (2017)), SINAR finds a nonlinear connection between multiple past states and future ones. SINAR allows for imposing a sparsity constraint onto the determination of macromodels in the same fashion as is done in SINDy for Markovian systems. This has already been done in a special way in Brunton et al. (2016), which is a special case of SINAR

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