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2、Translational Knowledge: From Collecting Data to Making Decisions in a Smart Grid 3、Characteristics of Fault Detection System for Smart Grid Distribution Network 4、Statistical Feature Selection From Massive Data in Distribution Fault Diagnosis 5、Computational Intelligence Algorithms Analysis for Smart Grid Cyber Security 6、Post evaluation index system of smart grid pilot city planning 7、Modeling and simulation of the communication networks in Smart grid 1、Arulampalam, M. S., et al.A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Transactions on Signal Processing, 50, 2 (Feb.2002), 174—188. 2、Agnoli, A., et al.Sensor fusion and estimation strategies for data traffic reduction in rooted wireless sensor networks.3rd International Symposium on Communications, Control and Signal Processing, Malta, Mar. 2008. 3、Bar-Shalom, A. Update with out-of-sequence measurements in tracking: Exact solution.IEEE Transactions on Aerospace and Electronic Systems,38, 3 (July 2002), 769—778. 4、Bar-Shalom, Y., Li, X. R., and Kirubarajan, T.Estimation with Applications to Tracking and Navigation:Theory, Algorithms and Software.Hoboken, NJ: Wiley, 2001.（书） 5、Bar-Shalom, Y., Mallick, M., and Chen, H.One-step solution for the general out-of-sequencemeasurement problem in tracking.IEEE Transactions on Aerospace and Electronic Systems,40, 1 (Jan. 2004), 27—37. 6、Blackman, S. S. and Popoli, R.Design and Analysis of Modern Tracking Systems.Norwood, MA: Artech House, 1999.（书） 7、Bresler, Y.Two-filter formulae for discrete-time non-linear Bayesian smoothing.International Journal of Control, 43, 2 (Feb. 1986),629—641. 8、Briers, M., Doucet, A., and Maskell, S.Smoothing algorithms for state-space models.Annals of the Institute of Statistical Mathematics, 62 (June2009), 61—89. 9、Chan, S. and Paffenroth, R.Out-of-sequence measurement updates formulti-hypothesis tracking algorithms.Proceedings of SPIE, Signal and Data Processing of SmallTargets, vol. 6969, Aug. 2008. 10、Carlin, B. P., Polson, N. G., and Stoffer, D. S.A Monte Carlo approach to nonnormal and nonlinearstate-space modeling.Journal of the American Statistical Association, 87, 418(1992), 493—500. 11、Doucet, A. and Johansen, A. M.A tutorial on particle filtering and smoothing: Fifteenyears later.Technical Report, Dept. of Statistics, University of BritishColumbia, 2008. 12、Jia, Z., Balasuriya, A., and Challa, S.Sensor fusion-based visual target tracking for autonomousvehicles with the out-of-sequence measurements solution.Journal on Robotics and Autonomous Systems, 56, 2 (Feb.2008). 13、Koch, W.On accumulated state densities with applications toout-of-sequence measurement processing.Proceedings of the 12th International Conference onInformation Fusion, Seattle, WA, July 2009. 14、Klaas, M., et al.Fast particle smoothing: If I had a million particles.Proceedings of the 23rd International Conference onMachine Learning, Pittsburgh, PA, 2006. 15、Koplin, M. and Elmenreich, W.Analysis of Kalman filter based approaches for fusingout-of-sequence measurements corrupted by systematic errors.IEEE International Conference on Multisensor Fusion andIntegration for Intelligent Systems, Seoul, Korea, Aug.2008. 16、Kitagawa, G.Monte Carlo filter and smoother for non-Gaussian nonlinear state space models.Journal of Computational and Graphical Statistics, 5, 1(1996), 1—25. 17、Mallick, M., Kirubarajan, T., and Arulampalam, S.Out-of-sequence measurement processing for trackingground target using particle filters.Proceedings of 2002 IEEE Aerospace Conference, Big Sky,MT, 2002. 18、Mallick, M. and Zhang, K. S.Optimal multiple-lag out-of-sequence measurement algorithm based on generalized smoothing framework.Proceedings of SPIE, Signal and Data Processing of SmallTargets, vol. 5913, San Diego, CA, Aug. 2005. 19、Muntzinger, M. M., et al.Out-of-sequence measurement processing for an automotive pre-crash application.Proceedings of the International IEEE Conference onIntelligent Transportation Systems, St. Louis, MO, Oct.2009. 20、Nettleton, E. W. and Durrant-Whyte, H.Delayed and asequent data in decentralized sensing networks.Proceedings of SPIE, Signal and Data Processing of SmallTargets, vol. 4571, Nov. 2001. 21、Orton, M. and Marrs, A.Particle filters for tracking with out-of-sequence measurements.IEEE Transactions on Aerospace and Electronic Systems,41, 2 (2005), 693—702. 22、Orguner, U. and Gustafsson, F.Storage efficient particle filters for the out of sequence measurement problem.Proceedings of the 11th International Conference onInformation Fusion, Cologne, June 2008, pp. 1—8. 23、Rauch, H., Tung, F., and Striebel, C.Maximum likelihood estimates of linear dynamic systems.AIAA Journal, 3, 8 (1965), 1445—1450. 24、Tichavsky, P., Muravchik, C. H., and Nehorai, A.Posterior Cramer-Rao bounds for discrete-time nonlinear filtering.IEEE Transactions on Signal Processing, 46, 5 (May1998), 1386—1396. 25、Zhang, K., Li, X. R., and Zhu, Y.Optimal update with out-of-sequence measurements for distributed filtering.IEEE Transactions on Signal Processing, 53, 6 (June2005), 1992—2004. 26、Zhang, S. and Bar-Shalom, Y.Optimal update with multiple out-of-sequence measurements with arbitrary arriving order.Submitted to IEEE Transactions on Aerospace andElectronic Systems. 27、Zhang, S., Bar-Shalom, Y., and Watson, G. Tracking with multisensor out-of-sequence measurements with residual biases.Proceedings of the 13th International Conference onInformation Fusion, Edinburgh, Scotland, July 2010. 28、Li, W., Jia, Y.: ‘Risk-sensitive filtering and smoothing for jumpMarkov non-linear systems based on unscented transform’, IETControl Theory Appl., 2009, 4, (11), pp. 2621–2630 29、A Two-Step Method for Out-of-Sequence Measurements.[ Last edited by eddy1211 on 2013-4-25 at 01:05 ] |
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