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Volumn 19, Issue 7, 2008, Pages 1154-1166

Distributed EM algorithm for Gaussian mixtures in sensor networks

Author keywords

Consensus filter; Distributed estimation; Distributed expectation maximization (EM) algorithm; Sensor networks

Indexed keywords

ALGORITHMS; APPROXIMATION ALGORITHMS; ARRAY PROCESSING; BOOLEAN FUNCTIONS; DETECTORS; ESTIMATION; PARAMETER ESTIMATION; SENSORS; STANDARDS; STATISTICAL METHODS; STATISTICS; TELECOMMUNICATION EQUIPMENT; TRELLIS CODES; WAVE FILTERS;

EID: 48949116234     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2008.915110     Document Type: Article
Times cited : (153)

References (30)
  • 3
    • 0042164384 scopus 로고    scopus 로고
    • Distributed EM algorithms for density estimation and clustering in sensor networks
    • Aug
    • R. D. Nowak, "Distributed EM algorithms for density estimation and clustering in sensor networks," IEEE Trans. Signal PIrocess., vol. 51, no. 8, pp. 2245-2253, Aug. 2003.
    • (2003) IEEE Trans. Signal PIrocess , vol.51 , Issue.8 , pp. 2245-2253
    • Nowak, R.D.1
  • 4
    • 33744915783 scopus 로고    scopus 로고
    • Distributed particle filter with GMM approximation for multiple targets localization and tracking in wireless sensor networks
    • Los Angeles, CA, Apr
    • Y. Sheng, X. Hu, and P. Ramanathan, "Distributed particle filter with GMM approximation for multiple targets localization and tracking in wireless sensor networks," in Proc. 4th Int. Symp. Inf. Process. Sensor Netw., Los Angeles, CA, Apr. 2005, pp. 181-188.
    • (2005) Proc. 4th Int. Symp. Inf. Process. Sensor Netw , pp. 181-188
    • Sheng, Y.1    Hu, X.2    Ramanathan, P.3
  • 5
    • 33747068503 scopus 로고    scopus 로고
    • Cooperative information maximization with Gaussian activation functions for self-organizing maps
    • Jul
    • R. Kamimura, "Cooperative information maximization with Gaussian activation functions for self-organizing maps," IEEE Trans. Neural Netw., vol. 17, no. 4, pp. 909-918, Jul. 2006.
    • (2006) IEEE Trans. Neural Netw , vol.17 , Issue.4 , pp. 909-918
    • Kamimura, R.1
  • 6
    • 34248648503 scopus 로고    scopus 로고
    • Unsupervised learning of Gaussian mixtures based on variational component splitting
    • May
    • C. Constantinopoulos and A. Likas, "Unsupervised learning of Gaussian mixtures based on variational component splitting," IEEE Trans. Neural Netw., vol. 18, no. 3, pp. 745-755, May 2007.
    • (2007) IEEE Trans. Neural Netw , vol.18 , Issue.3 , pp. 745-755
    • Constantinopoulos, C.1    Likas, A.2
  • 7
    • 33746371214 scopus 로고    scopus 로고
    • A kernel-based learning approach to ad hoc sensor network localization
    • X. Nguyen, M. I. Jordan, and B. Sinopoli, "A kernel-based learning approach to ad hoc sensor network localization," ACM Trans. Sensor Netw., vol. 1, no. 1, pp. 134-152, 2005.
    • (2005) ACM Trans. Sensor Netw , vol.1 , Issue.1 , pp. 134-152
    • Nguyen, X.1    Jordan, M.I.2    Sinopoli, B.3
  • 8
    • 3042699000 scopus 로고    scopus 로고
    • A learning theory approach to sensor networks
    • Oct./Dec
    • S. Simic, "A learning theory approach to sensor networks," IEEE Pervasive Comput., vol. 2, no. 4, pp. 44-49, Oct./Dec. 2003.
    • (2003) IEEE Pervasive Comput , vol.2 , Issue.4 , pp. 44-49
    • Simic, S.1
  • 10
    • 0000262562 scopus 로고
    • Hierarchical mixtures of experts and the EM algorithm
    • M. I. Jordan and R. A. Jacobs, "Hierarchical mixtures of experts and the EM algorithm," Neural Comput., vol. 6. pp. 181-214. 1994.
    • (1994) Neural Comput , vol.6 , pp. 181-214
    • Jordan, M.I.1    Jacobs, R.A.2
  • 11
    • 0026938712 scopus 로고
    • The mean field theory in EM procedures for Markov random fields
    • Mar
    • J. Zhang, "The mean field theory in EM procedures for Markov random fields," IEEE Trans. Signal Process., vol. 40, no. 3, pp. 2570-2583, Mar. 1992.
    • (1992) IEEE Trans. Signal Process , vol.40 , Issue.3 , pp. 2570-2583
    • Zhang, J.1
  • 12
    • 0037209490 scopus 로고    scopus 로고
    • EM procedures using mean field-like approximations for Markov model-based image segmentation
    • G. Celeux, F. Forbes, and N. Peyrard, "EM procedures using mean field-like approximations for Markov model-based image segmentation," Pattern Recognit., vol. 36, pp. 131-144, 2003.
    • (2003) Pattern Recognit , vol.36 , pp. 131-144
    • Celeux, G.1    Forbes, F.2    Peyrard, N.3
  • 13
    • 34248678480 scopus 로고    scopus 로고
    • A spatially constrained generative model and an EM algorithm for image segmentation
    • May
    • A. Diplaros, N. Vlassis, and T. Gevers, "A spatially constrained generative model and an EM algorithm for image segmentation," IEEE Trans. Neural Netw., vol. 18, no. 3, pp. 798-808, May 2007.
    • (2007) IEEE Trans. Neural Netw , vol.18 , Issue.3 , pp. 798-808
    • Diplaros, A.1    Vlassis, N.2    Gevers, T.3
  • 14
    • 85032751029 scopus 로고    scopus 로고
    • Information-driven dynamic sensor collaboration for tracking applications
    • Mar
    • F. Zhao, J. Shin, and J. Reich, "Information-driven dynamic sensor collaboration for tracking applications," IEEE Signal Process. Mag. vol. 19, no. 2, pp. 61-72, Mar. 2002.
    • (2002) IEEE Signal Process. Mag , vol.19 , Issue.2 , pp. 61-72
    • Zhao, F.1    Shin, J.2    Reich, J.3
  • 15
    • 33645001047 scopus 로고    scopus 로고
    • Distributed Kalman filter with embedded consensus filters
    • Dec. 12-15
    • R. Olfati-Saber, "Distributed Kalman filter with embedded consensus filters," in Proc. 44th IEEE Conf. Decision Control, Dec. 12-15, 2005, pp. 8179-8184.
    • (2005) Proc. 44th IEEE Conf. Decision Control , pp. 8179-8184
    • Olfati-Saber, R.1
  • 16
    • 0002629270 scopus 로고
    • Maximum likelihood estimation from incomplete data via the EM algorithm
    • A. Dempster, N. Laird, and D. Rubin, "Maximum likelihood estimation from incomplete data via the EM algorithm," J. Roy. Statist. Soc. vol. 39, pp. 1-38, 1977.
    • (1977) J. Roy. Statist. Soc , vol.39 , pp. 1-38
    • Dempster, A.1    Laird, N.2    Rubin, D.3
  • 17
    • 33747142749 scopus 로고    scopus 로고
    • The capacity of wireless networks
    • May
    • P. Gupta and P. R. Kumar, "The capacity of wireless networks," IEEE Trans. Inf. Theory, vol. 46, no. 3, pp. 388-404, May 2000.
    • (2000) IEEE Trans. Inf. Theory , vol.46 , Issue.3 , pp. 388-404
    • Gupta, P.1    Kumar, P.R.2
  • 18
    • 0002788893 scopus 로고    scopus 로고
    • A view of the EM algorithm that justifies incremental, sparse, and other variants
    • M. I. Jordan, Ed. Boston, MA: Kluwer
    • R. M. Neal and G. E. Hinton, "A view of the EM algorithm that justifies incremental, sparse, and other variants," in Learning in Graphical Models, M. I. Jordan, Ed. Boston, MA: Kluwer, 1998, pp. 355-368.
    • (1998) Learning in Graphical Models , pp. 355-368
    • Neal, R.M.1    Hinton, G.E.2
  • 19
    • 33746234422 scopus 로고    scopus 로고
    • Consensus filters for sensor networks works and distributed sensor fusion
    • Dec. 12-15
    • R. Olfati-Saber and J. S. Shamma, "Consensus filters for sensor networks works and distributed sensor fusion," in Proc. 44th IEEE Conf. Decision Control, Dec. 12-15, 2005, pp. 6698-6703.
    • (2005) Proc. 44th IEEE Conf. Decision Control , pp. 6698-6703
    • Olfati-Saber, R.1    Shamma, J.S.2
  • 20
    • 20344399896 scopus 로고    scopus 로고
    • Consensus seeking in multiagent systems under dynamically changing interaction topologies
    • May
    • W. Ren and R. W. Beard, "Consensus seeking in multiagent systems under dynamically changing interaction topologies," IEEE Trans. Autom. Control, vol. 50, no. 5, pp. 655-661, May 2005.
    • (2005) IEEE Trans. Autom. Control , vol.50 , Issue.5 , pp. 655-661
    • Ren, W.1    Beard, R.W.2
  • 21
    • 2342533082 scopus 로고    scopus 로고
    • On convergence properties of the EM algorithm for Gaussian mixtures
    • L. Xu and M. I. Jordan, "On convergence properties of the EM algorithm for Gaussian mixtures," Neural Comput., vol. 8, pp. 129-151, 1996.
    • (1996) Neural Comput , vol.8 , pp. 129-151
    • Xu, L.1    Jordan, M.I.2
  • 22
    • 0034131785 scopus 로고    scopus 로고
    • On-line EM algorithm for the normalized Guassian network
    • M. Sato and S. Ishii, "On-line EM algorithm for the normalized Guassian network," Neural Comput., vol. 12, pp. 407-432, 2000.
    • (2000) Neural Comput , vol.12 , pp. 407-432
    • Sato, M.1    Ishii, S.2
  • 24
    • 0036522404 scopus 로고    scopus 로고
    • Unsupervised learning of finite mixture models
    • Mar
    • M. A. T. Figueiredo and A. K. Jain, "Unsupervised learning of finite mixture models," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 3, pp. 381-396, Mar. 2002.
    • (2002) IEEE Trans. Pattern Anal. Mach. Intell , vol.24 , Issue.3 , pp. 381-396
    • Figueiredo, M.A.T.1    Jain, A.K.2
  • 25
    • 48949110337 scopus 로고    scopus 로고
    • N. A. Lynch, Distributed, Algorithms. San Francisco, CA: Morgan Kaufmann, 1996.
    • N. A. Lynch, Distributed, Algorithms. San Francisco, CA: Morgan Kaufmann, 1996.
  • 26
    • 4644244041 scopus 로고    scopus 로고
    • Consensus problems in networks of agents with switching topology and time-delay
    • Sep
    • R. Olfati-Saber and R. M. Murray, "Consensus problems in networks of agents with switching topology and time-delay," IEEE Trans. Autom. Control, vol. 49, no. 9, pp. 101-115, Sep. 2004.
    • (2004) IEEE Trans. Autom. Control , vol.49 , Issue.9 , pp. 101-115
    • Olfati-Saber, R.1    Murray, R.M.2
  • 28
    • 11344275321 scopus 로고    scopus 로고
    • Fastest mixing Markov chain on a graph
    • Dec
    • S. Boyd. P. Diaconis, and L. Xiao, "Fastest mixing Markov chain on a graph," SIAM Rev., vol. 46, no. 4, pp. 667-689, Dec. 2004.
    • (2004) SIAM Rev , vol.46 , Issue.4 , pp. 667-689
    • Boyd, S.1    Diaconis, P.2    Xiao, L.3
  • 29
    • 0036475447 scopus 로고    scopus 로고
    • A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
    • Feb
    • M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp. "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Trans. Signal Process., vol. 50, no. 2, pp. 174-188, Feb. 2002.
    • (2002) IEEE Trans. Signal Process , vol.50 , Issue.2 , pp. 174-188
    • Arulampalam, M.S.1    Maskell, S.2    Gordon, N.3    Clapp, T.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.