Year: 2025
Type: article
Abstract: The Yau-Yau nonlinear filter has increasingly emerged as a powerful tool to study stochastic complex systems.To leverage it to a wider spectrum of application scenarios, we pack the Yau-Yau filtering ALgorithms (YauYauAL) into a package of computer software.Yau-YauAL was written in R, designed to simplify the implementation of the Yau-Yau filter for solving nonlinear filtering problems.Combining R's accessibility with C++ (via Rcpp) for computational efficiency, YauYauAL provides an intuitive Shinybased interface that enables real-time parameter adjustment and result visualization.At its core, YauYauAL employs finite difference methods to numerically solve the Kolmogorov forward equation, ensuring a stable and accurate solution even for complex systems.YauYauAL's modular design and open-source framework further encourage customization and community-driven development.YauYauAL aims to bridge the gap between theoretical nonlinear filtering methods and practical applications, without requiring expertise in differential equation solving or programming, fostering its broader impact on various scientific fields, such as signal processing, finance, medicine, and biology among a long list.
Source: Data Analytics and Topology
Authors: Yu Wang, Shuyuan Xu, Xueda Wei, Xinrui Luo, Stephen Shing-Toung Yau, Shing-Tung Yau, Rongling Wu
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Award: G8215032062
OpenAlex ID: W4411333112