Binary spatial random field reconstruction from non-Gaussian inhomogeneous time-series observations

• Main Authors: Sheng, Shunan, Xiang, Qikun, Nevat, Ido, Neufeld, Ariel
• 其他作者: School of Physical and Mathematical Sciences
• 格式: Article
• 語言: English
• 出版: 2024
• 主題: Mathematical Sciences; Sensor networks; Warped Gaussian process
• 在線閱讀: https://hdl.handle.net/10356/176210
• 機構: Nanyang Technological University

We develop a new model for spatial random field reconstruction of a binary-valued spatial phenomenon. In our model, sensors are deployed in a wireless sensor network across a large geographical region. Each sensor measures a non-Gaussian inhomogeneous temporal process which depends on the spatial ph...