Yau-YauAL: A computer tool for solving nonlinear filtering problems

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.

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Publication Details

Journal
Data Analytics and Topology
Published
2025-01-01
DOI
https://doi.org/10.4310/daat.250617012448
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Yau-YauAL: A computer tool for solving nonlinear filtering problems

Xing Wei, Stephen S.‐T. Yau, Xinrui Luo, Shuyuan Xu et al.
Data Analytics and Topology
Neural Networks and Applications
article

Yau-YauAL: A computer tool for solving nonlinear filtering problems

Xing Wei, Stephen S.‐T. Yau, Xinrui Luo, Shuyuan Xu, Rongling Wu, Yu Wang, Shing‐Tung Yau
article en

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.

Data Analytics and TopologyVol. 1(1)
Inner Mongolia Normal University (CN), Beijing Normal University (CN), Academy of Mathematics and Systems Science (CN), University of Chinese Academy of Sciences (CN), Beijing Institute of Mathematical Sciences and Applications, Renmin University of China (CN), Tsinghua University (CN)
Chinese Academy of Sciences, Tsinghua University, Renmin University of China, Natural Science Foundation of Inner Mongolia, Division of Mathematical Sciences
Openalex Percentile: Top 93%
Neural Networks and Applications
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