Root cause diagnosis can locate abnormalities of industrial processes, ensuring production
safety and manufacturing efficiency. However, existing root cause diagnosis models only …

This paper provides an overview of results and concepts in minimax robust hypothesis
testing for two and multiple hypotheses. It starts with an introduction to the subject …

The modeling and forecasting of cerebral pressure–flow dynamics in the time–frequency
domain have promising implications for veterinary and human life sciences research …

大容量, 高参数, 低能耗的百万千瓦超超临界机组是燃煤发电领域的重大装备,
已成为全国电力工业发展的主流方向, 其安全可靠运行对推动发电企业转型升级具有重要意义 …

Time-varying directed electroencephalography (EEG) network is the potential tool for
studying the dynamical causality among brain areas at a millisecond level; which conduces …

This study proposes a new parametric time-frequency conditional Granger causality (TF-
CGC) method for high-precision connectivity analysis over time and frequency domain in …

Due to the interaction of process variables, process data is in essence graph-structured with
non-Euclidean nature. Hence, learning the graph representation in a low-dimensional …

Objective. Electroencephalogram (EEG)-based motor imagery (MI) brain-computer interface
offers a promising way to improve the efficiency of motor rehabilitation and motor skill …

Objective: Post-stroke transcranial magnetic stimulation (TMS) has gradually become a
brain intervention to assist patients in the recovery of motor function. The long lasting …

Root cause diagnosis (RCD) is an important technique for maintaining process safety, which
infers the causalities between faulty measurements to locate the root cause of the fault …