Computing the block triangular form of a sparse matrix
ACM Transactions on Mathematical Software (TOMS)
Readings in model-based diagnosis
Readings in model-based diagnosis
Diagnosis with behavioral modes
Readings in model-based diagnosis
What's in SD?: Towards a theory of modeling for diagnosis
Readings in model-based diagnosis
Hierarchical model-based diagnosis based on structural abstraction
Artificial Intelligence
Diagnosis and Fault-Tolerant Control
Diagnosis and Fault-Tolerant Control
Principles of Constraint Programming
Principles of Constraint Programming
Redundancy Relations for Fault Diagnosis in Nonlinear Uncertain Systems
International Journal of Applied Mathematics and Computer Science
An Efficient Algorithm for Finding Minimal Overconstrained Subsystems for Model-Based Diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Robotics and Computer-Integrated Manufacturing
Minimizing test-point allocation to improve diagnosability in business process models
Journal of Systems and Software
| Hi-index | 0.00 |
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA, which is based on the estimation of the sample mean and covariance matrix of the data, is very sensitive to outliers in the training data ...