A review on data-driven process monitoring methods: Characterization and mining of industrial data
Safe and stable operation plays an important role in the chemical industry. Fault detection
and diagnosis (FDD) make it possible to identify abnormal process deviations early and …
and diagnosis (FDD) make it possible to identify abnormal process deviations early and …
Data-driven causal analysis of observational biological time series
Complex systems are challenging to understand, especially when they defy manipulative
experiments for practical or ethical reasons. Several fields have developed parallel …
experiments for practical or ethical reasons. Several fields have developed parallel …
Causal connectivity measures for pulse-output network reconstruction: Analysis and applications
ZK Tian, K Chen, S Li… - Proceedings of the …, 2024 - National Acad Sciences
The causal connectivity of a network is often inferred to understand network function. It is
arguably acknowledged that the inferred causal connectivity relies on the causality measure …
arguably acknowledged that the inferred causal connectivity relies on the causality measure …
The human organism as an integrated interaction network: recent conceptual and methodological challenges
The field of Network Physiology aims to advance our understanding of how physiological
systems and sub-systems interact to generate a variety of behaviors and distinct …
systems and sub-systems interact to generate a variety of behaviors and distinct …
Ordinal partition transition network based complexity measures for inferring coupling direction and delay from time series
It has been demonstrated that the construction of ordinal partition transition networks
(OPTNs) from time series provides a prospective approach to improve our understanding of …
(OPTNs) from time series provides a prospective approach to improve our understanding of …
Real-time industrial process fault diagnosis based on time delayed mutual information analysis
Causal relations among variables may change significantly due to different control strategies
and fault types. Off line-based knowledge is not adequate for fault diagnosis, and existing …
and fault types. Off line-based knowledge is not adequate for fault diagnosis, and existing …
Causal coupling inference from multivariate time series based on ordinal partition transition networks
Identifying causal relationships is a challenging yet crucial problem in many fields of science
like epidemiology, climatology, ecology, genomics, economics and neuroscience, to …
like epidemiology, climatology, ecology, genomics, economics and neuroscience, to …
Upper limb cortical-muscular coupling analysis based on time-delayed back maximum information coefficient model
In musculoskeletal systems, describing accurately the coupling direction and intensity
between physiological electrical signals is crucial. The maximum information coefficient …
between physiological electrical signals is crucial. The maximum information coefficient …
Identifying bidirectional total and non-linear information flow in functional corticomuscular coupling during a dorsiflexion task: a pilot study
T Liang, Q Zhang, X Liu, B Dong, X Liu… - … of NeuroEngineering and …, 2021 - Springer
Background The key challenge to constructing functional corticomuscular coupling (FCMC)
is to accurately identify the direction and strength of the information flow between scalp …
is to accurately identify the direction and strength of the information flow between scalp …
Directed information flow analysis reveals muscle fatigue-related changes in muscle networks and corticomuscular coupling
T Liang, Q Zhang, L Hong, X Liu, B Dong… - Frontiers in …, 2021 - frontiersin.org
As a common neurophysiological phenomenon, voluntary muscle fatigue is accompanied by
changes in both the central nervous system and peripheral muscles. Considering the …
changes in both the central nervous system and peripheral muscles. Considering the …