When Shannon Meets Nonstochastic Information: Communication and Estimation

• 成果类型: Article
• 署名作者: Zhang, Wentao; Zuo, Zhiqiang; Zhao, Rui; Wang, Yijing; Hu, Guoqiang; Zhang, Hui; Wang, Yaonan
• 署名单位: Hunan University; Nanyang Technological University; Tianjin University; Nanyang Technological University; Hunan University; Hunan University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3543563
• 发表日期: 2025
• 页码: 5444-5451
• 关键词: NOISE; uncertainty; entropy; ELECTRONIC MAIL; robots; Information theory; Visual perception; training; Random variables; Information rates; Channel capacity; nonstochastic information theory; State estimation

摘要

This note focuses on the issue of whether or not the state of a plant can be estimated when the inputs of communication channel involve noise and disturbance simultaneously. It turns out to calculate the maximum capacity of stationary memoryless M-MQAC under nonstochastic information theory. It is shown that the maximum information rate over such a channel is determined by a convex hull spanned by the zero-error capacities, which are specified on the underlying sample spaces. Moreover, the state of a plant could be estimated provided that the maximal information rate is strictly greater than the topology entropy.