Publicaciones en las que colabora con Gautam Biswas (13)

2014

  1. A common framework for compilation techniques applied to diagnosis of linear dynamic systems

    IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 44, Núm. 7, pp. 863-876

  2. An event-based distributed diagnosis framework using structural model decomposition

    Artificial Intelligence, Vol. 210, Núm. 1, pp. 1-35

2012

  1. A decomposition method for nonlinear parameter estimation in TRANSCEND

    IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, Vol. 42, Núm. 3, pp. 751-763

  2. Diagnosability analysis considering causal interpretations for differential constraints

    IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, Vol. 42, Núm. 5, pp. 1216-1229

  3. Fault diagnosis in hybrid systems using possible conflicts

    IFAC Proceedings Volumes (IFAC-PapersOnline)

  4. Improving multiple fault diagnosability using possible conflicts

    IFAC Proceedings Volumes (IFAC-PapersOnline)

2011

  1. Dynamic Bayesian Network Factors from Possible Conflicts for Continuous System Diagnosis

    Advances in Artificial Intelligence: 14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2011, La Laguna, Spain, November 7-11, 2011. Proceedings

  2. Dynamic Bayesian network factors from possible conflicts for continuous system diagnosis

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Structural diagnosability analysis of dynamic models

    IFAC Proceedings Volumes (IFAC-PapersOnline)

2009

  1. Analytic redundancy, possible conflicts, and TCG-based fault signature diagnosis applied to nonlinear dynamic systems

    IFAC Proceedings Volumes (IFAC-PapersOnline)

  2. Efficient on-line parameter estimation in TRANSCEND for nonlinear systems

    Annual Conference of the Prognostics and Health Management Society, PHM 2009

  3. Generating possible conflicts from bond graphs using temporal causal graphs

    Proceedings - 23rd European Conference on Modelling and Simulation, ECMS 2009