Data-Based Reconstruction of Chaotic Systems by Stochastic Iterative Greedy Algorithm

It is challenging to reconstruct a nonlinear dynamical system when sufficient observations are not available. Recent study shows this problem can be solved by paradigm of compressive sensing. In this paper, we study the reconstruction of chaotic systems based on the stochastic gradient matching purs...

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Veröffentlicht in:	Mathematical problems in engineering 2020, Vol.2020 (2020), p.1-9
Hauptverfasser:	Xiao, Yuzhu, Song, Xueli, Dong, Guoli
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Chaos theory Computational geometry Convex analysis Convexity Dynamical systems Greedy algorithms Iterative methods Matched pursuit Mathematical problems Methods Optimization Parameter identification Reconstruction Sparsity Success
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