Enhancing spectral analysis in nonlinear dynamics with pseudoeigenfunctions from continuous spectra
Itsushi Sakata,
Yoshinobu Kawahara
Abstract:The analysis of complex behavior in empirical data poses significant challenges in various scientific and engineering disciplines. Dynamic Mode Decomposition (DMD) is a widely used method to reveal the spectral features of nonlinear dynamical systems without prior knowledge. However, because of its infinite dimensions, analyzing the continuous spectrum resulting from chaos and noise is problematic. We propose a clustering-based method to analyze dynamics represented by pseudoeigenfunctions associated with cont… Show more
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