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Journal Article
IEEE Transactions on Cybernetics, ISSN 2168-2267, 06/2015, Volume 45, Issue 6, pp. 1209 - 1221
Journal Article
IEEE Transactions on Signal Processing, ISSN 1053-587X, 11/2002, Volume 50, Issue 11, pp. 2744 - 2756
Journal Article
IEEE Transactions on Automatic Control, ISSN 0018-9286, 7/2019, pp. 1 - 1
Despite the correct-by-construction property, one of the major drawbacks of supervisory control synthesis is state-space explosion. Several approaches have... 
dependency structure matrices | extended finite automata | Automata | Transforms | multilevel discrete-event systems | Supervisory control | Markov processes | Discrete-event systems | Modeling
Journal Article
IEEE Transactions on Smart Grid, ISSN 1949-3053, 06/2011, Volume 2, Issue 2, pp. 342 - 351
Fault diagnosis in power grids is known to be challenging, due to the massive scale and spatial coupling therein. In this study, we explore multiscale network... 
Dependency graph | Correlation | Power transmission lines | multiscale decomposition | smart grid | Fault detection | fault localization | Markov processes | Transmission line measurements | network inference | Random variables | Markov random field | MARKOV RANDOM-FIELD | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
IEEE Transactions on Information Theory, ISSN 0018-9448, 02/2009, Volume 55, Issue 2, pp. 816 - 827
Journal Article
Pattern Recognition Letters, ISSN 0167-8655, 08/2018, Volume 111, pp. 23 - 29
One of the most effective structure-learning methods in a Bayesian network is the K2 algorithm. Because the performance of the K2 algorithm depends on the node... 
Dependency criterion | Bayesian network | L1-regularized Markov Blanket | SELECTION | BAYESIAN NETWORK STRUCTURES | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Usage | Algorithms | Management | Information technology | Analysis
Journal Article
Neural Computing and Applications, ISSN 0941-0643, 10/2019, Volume 31, Issue 10, pp. 6795 - 6805
Journal Article
Mechanical Systems and Signal Processing, ISSN 0888-3270, 05/2018, Volume 105, pp. 467 - 480
It is widely noted in the literature that the degradation should be simplified into a memoryless Markovian process for the purpose of predicting the remaining... 
Weak convergence | Maximum likelihood | Remaining useful life | Fractional Brownian motion | Non-Markovian diffusion process | FRACTIONAL BROWNIAN-MOTION | SYSTEMS | ENGINEERING, MECHANICAL | PREDICTION
Journal Article
Pattern Recognition Letters, ISSN 0167-8655, 08/2018, Volume 111, p. 23
One of the most effective structure-learning methods in a Bayesian network is the K2 algorithm. Because the performance of the K2 algorithm depends on the node... 
Algorithms | Parents | Machine learning | Dependence | Markov processes | Pattern recognition | Markov analysis | Criteria | Bayesian analysis | Nodes
Journal Article
Science China Information Sciences, ISSN 1674-733X, 5/2018, Volume 61, Issue 5, pp. 1 - 16
Characterizing and understanding the structure and the evolution of networks is an important problem for many different fields. While in the real-world... 
time lag | Information Systems and Communication Service | dependency network | dynamic network | Computer Science | COMPUTER SCIENCE, INFORMATION SYSTEMS | MODEL | SELECTION | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
Performance Evaluation, ISSN 0166-5316, 04/2017, Volume 110, pp. 22 - 47
Marking dependency is a powerful tool that allows different firing time distributions to be associated with a stochastic Petri net transition, depending on the... 
Non-Markovian stochastic Petri nets | Kronecker algebra | Multi-core CPUs | Phase type distributions | Power management | Marking dependency | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | POLICIES | DIFFUSION-APPROXIMATION | PRODUCT-FORM | MODELS | AVAILABILITY | FRAMEWORK | COMPUTER SCIENCE, THEORY & METHODS | Case studies | Markov processes | Algebra | Analysis
Journal Article