基于提升小波变换的布朗运动的生成算法
Generated Algorithm for Brown Motion Based on Lifting Wavelet Transform
DOI: 10.12677/pm.2024.143099, PDF,   
作者: 曹航宾:新疆师范大学数学科学学院,新疆 乌鲁木齐;周小辉:上海财经大学浙江学院,浙江 金华
关键词: 分形整合过程提升小波变换Brown运动Fractal Integration Process Improve Wavelet Transform Brown Motion
摘要: 文中基于提升小波系数,首先提出了一种生成标准正态随机数的新方法与多维Brown运动生成算法,且给出了1维,2维与3维情形的模拟。然后将小波系数应用于金融模型中,利用小波系数讨论了典范双因子Vasicek模型。最后给出了显式表达式和数值模拟。
Abstract: Based on the wavelet coefficients, a new method for generating standard normal random numbers and a new generation algorithm for multi-dimensional Brown motion are proposed in this paper. And some numerical simulations are given in one-dimensional, two-dimensional and three-dimensional cases. Then the wavelet coefficients are applied in the financial model. The canonical two-factor Vasicek model is discussed by wavelet coefficients. The explicit expressions and numerical simulation are given finally.
文章引用:曹航宾, 周小辉. 基于提升小波变换的布朗运动的生成算法[J]. 理论数学, 2024, 14(3): 201-210. https://doi.org/10.12677/pm.2024.143099

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