Toward Fitting Structured Nonlinear Systems by Means of Dynamic Mode Decomposition
نویسندگان
چکیده
The dynamic mode decomposition (DMD) is a data-driven method used for identifying the dynamics of complex nonlinear systems. It extracts important characteristics underlying using measured time-domain data produced either by means experiments or numerical simulations. In original methodology, measurements are assumed to be approximately related linear operator. Hence, discrete-time system fitted given data. However, often, systems modeling physical phenomena have particular known structure. this contribution, we propose an identification and reduction based on classical DMD approach allowing fit structured We mainly focus two types nonlinearities: bilinear quadratic bilinear. By enforcing additional structure, more insight into extracting behavior process gained. Finally, demonstrate proposed methodology different examples, such as Burgers’ equation coupled van der Pol oscillators.
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ژورنال
عنوان ژورنال: International series of numerical mathematics
سال: 2021
ISSN: ['0373-3149', '2296-6072']
DOI: https://doi.org/10.1007/978-3-030-72983-7_3