Distributed Bayesian fault diagnosis of jump Markov systems in wireless sensor networks

International Journal of Sensor Networks

Volumn 2, Issue 1-2, 2007, Pages 118-127

  Snoussi, Hichem ^a   Richard, Cédric ^a  

^a UNIVERSITÉ DE TECHNOLOGIE DE TROYES   (France)

Author keywords

Collaborative sensor network; Online change detection; Rao blackwellised particle filter; RB CPF

Indexed keywords

BANDPASS FILTERS; BAYESIAN NETWORKS; DATA HANDLING; DISTRIBUTED COMPUTER SYSTEMS; DYNAMICAL SYSTEMS; ECONOMIC AND SOCIAL EFFECTS; FAULT DETECTION; KALMAN FILTERS; ONLINE SYSTEMS; SENSOR NODES; STATE SPACE METHODS;

BAYESIAN; COLLABORATIVE SENSOR NETWORKS; DISCRETE STATE; FAULTS DIAGNOSIS; JUMP MARKOV SYSTEM; OBSERVED SYSTEMS; ONLINE CHANGE DETECTION; PARTICLE FILTER; RAO-BLACKWELLISED COLLABORATIVE PARTICLE FILTER; RAO-BLACKWELLISED PARTICLE FILTERS;

MONTE CARLO METHODS;

EID: 77949953826     PISSN: 17481279     EISSN: 17481287     Source Type: Journal    
DOI: 10.1504/IJSNET.2007.012990     Document Type: Article

References (17)

1. Andrieu, C., Doucet, A., Singh, S. and Tadic, V. (2004) 'Particle methods for change detection, system identification, and control', Proceedings of the IEEE, March, Vol. 92, No. 3, pp. 423-438.
2. de Freitas, N. (2002) 'Rao-Blackwellised particle filtering for fault diagnosis', IEEE Aerospace.
3. Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977) 'Maximum likelihood from incomplete data via the em algorithm', Journal of the Royal Statistical Society, Series B, Vol. 39, pp. 1-38.
4. Doucet, A., Godsill, S. and Andrieu, C. (2000) 'On sequential Monte Carlo sampling methods for Bayesian filtering', Statistics and Computing, Vol. 10, No. 3, pp. 197-208.
5. Doucet, A., de Freitas, N. and Gordon, N. (2001) Sequential Monte Carlo Methods in Practice, Springer-Verlag.
6. Doucet, A., Vo, B., Andrieu, C. and Davy, M. (2002) 'Particle filtering for multitarget tracking and sensor management', Proceedings of the International Conference on Information Fusion, Vol. 1, pp. 474-481.
7. Ihler, A., Fisher III, J. and Willsky, A. (2004) 'Using sample-based representations under communications constraints', Technical Report 2601, MIT, Laboratory for Information and Decision Systems.
8. Ihler, A., Fisher III, J. and Willsky, A. (2005) 'Particle filtering under communications constraints', Proceedings of Statistical Signal Processing (SSP).
9. Li, X. and Jilkov, V. (2003) 'Survey of maneuvering target tracking. Part i: dynamic models', IEEE Transactions on AES, Vol. 39, No. 4, pp. 1333-1364.
10. Li, X. and Jilkov, V. (2005) 'Survey of maneuvering target tracking. Part v: multiple-model methods', IEEE Transactions AES, Vol. 41, No. 4, pp. 1255-1321.
11. Pasha, A., Vo, B., Tuan, H. and Ma, W. (2006) 'Closed form filtering for linear jump Markov models', Proceedings of FUSION, Florence.
12. Roweis, S. and Ghahramani, Z. (1999) 'A unifying review of linear Gaussian models', Neural Computation, Vol. 11, No. 2, p. 305.
13. Special Issue (2002) 'Collaborative information processing', IEEE Signal Processing Magazine, Vol. 19, No. 2.
14. Special Issue (2005) 'Special issue on self-organizing distributed collaborative sensor networks', IEEE Journal on Selected Areas in Communications, Vol. 23, No. 4.
15. Special Issue (2006) 'Distributed signal processing in sensor networks', IEEE Signal Processing Magazine, Vol. 16.
16. Sheng, X., Hu, Y. and Ramanathan, P. (2005) 'Distributed particle filter with GMM approximation for multiple targets localization and tracking ion wireless sensor network', Information Processing in Sensor Networks. IPSN'05, pp. 181-188.
17. Washington, R. (2000) 'On-board real-time state and fault identification for rovers', IEEE International Conference on Robotics and Automation.