The content discusses the application of Weak Collocation Regression (WCR) to infer stochastic dynamics with Lévy noise. The method is compared to existing approaches, showcasing improved accuracy and efficiency. Various multi-dimensional scenarios are explored, highlighting the effectiveness of WCR in distinguishing different types of noises.
The content emphasizes the importance of considering Lévy noise in stochastic systems due to its ability to capture heavy-tailed distributions and jumps. The experiments demonstrate the superior performance of WCR over previous methods in terms of accuracy and computational efficiency. Multi-dimensional problems are also addressed, showcasing the versatility of WCR in handling complex scenarios.
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by Liya Guo,Liw... at arxiv.org 03-14-2024
https://arxiv.org/pdf/2403.08292.pdfDeeper Inquiries