Electrical computers and digital processing systems: multicomput – Computer network managing – Computer network monitoring
Reexamination Certificate
2011-08-30
2011-08-30
Barqadle, Yasin (Department: 2456)
Electrical computers and digital processing systems: multicomput
Computer network managing
Computer network monitoring
C709S203000, C709S206000, C709S223000, C382S103000, C382S154000, C382S187000
Reexamination Certificate
active
08010658
ABSTRACT:
According to one embodiment, a computing system includes a computing node coupled to a number of sensors. The sensors are operable to generate records from received information and transmit these records to the computing node. The computing node is operable to bind the plurality of records in a plurality of classifications using a multiple level classifier such that each classification has a differing level of specificity.
REFERENCES:
patent: 5842156 (1998-11-01), Hong et al.
patent: 6014447 (2000-01-01), Kohnen et al.
patent: 6269324 (2001-07-01), Rakijas et al.
patent: 6393137 (2002-05-01), Chen et al.
patent: 6829568 (2004-12-01), Julier et al.
patent: 7005981 (2006-02-01), Wade
patent: 7035764 (2006-04-01), Rui et al.
patent: 1 596 334 (2005-11-01), None
L.Xiao, S. Boyd, S. Lall, “A Scheme for Robust Distributed Sensor Fusion Based on Average Consensus,”Information Processing in Sensor Networks, pp. 63-70, Apr. 15, 2005.
K. Kastella, “Discrimination Gain to Optimize Detection and Classification,”IEEE Transactions on Systems, Man, and Cybernetics, Part A, Systems and Humans, vol. 27, No. 1, pp. 112-116, Jan. 1997.
V. Krishnamurthy, D. Evans, “Hidden Markov Model Multiarm Bandits; a Methodology for Beam Scheduling in Multitarget Tracking,”IEEE Trans. Signal Process. (pp. 2893-2908), 2001.
D. P. Bertsekas, D. Castanon, “Rollout Algorithms for Stochastic Scheduling Problems,”J. Heuristics, pp. 1-25, 1998.
M. K. Schneider, G.L. Mealy, and F. M. Pait, “Closing the Loop in Sensor Fusion Systems; Stochastic Dynamic Programming Approaches,”Proceedings of the 2004 American Control Conf, vol. 5, pp. 4752-4757, 2004.
R. E. Kalman, “A New Approach to Linear Filtering and Prediction Problems,”Transactions of the ASME—Journal of Basic Engineering 82(D), 12 pages, 1960.
M. J. Kearns, Y. Mansour, and A.Y. Ng, “A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes,”Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 8 pages, 1999.
A. Makarenko, H.F. Durrant-Whyte, “Decentralized Data Fusion and Control in Active Sensor Networks,”7th Int. Conf on Info Fusion, 8 pages, 2004.
A. D'Costa, A. M. Sayeed, “Data Versus Decision Fusion for Distributed Classification in Sensor Networks,”Military Communications Conference, pp. 890-894, 2003.
T. Clouquer, P. Ramanthan, K.K. Saluja, K. Wang, “Value-Fusion versus Decision-Fusion for Fault-Tolerance in Collaborative Target Detection in Sensor Networks,”Proceedings of Fourth International Conference on Information Fusio, 6 pages, Aug. 2001.
X. Wang, G. Foliente, Z. Su, L. Ye, “Multilevel Decision Fusion in a Distributed Active Sensor Network for Structural Damage Detection,”Structural Health Monitoring, pp. 45-58, 2006.
A. W. Stroupe, M.C. Martin, T. Balch, “Distributed Sensor Fusion for Object Position Estimation by Multi-Robot Systems,”Robotics and Automation, pp. 1092-1098, vol. 2, 2001.
R. R. Brooks, P. Ramanthan, A. M. Sayeed, “Distributed Target Classification and Tracking in Sensor Networks,”Signal Processing Magazine, IEEE, pp. 1163-1171, 2003.
H. Qi, X. Wang, S.S. Iyengar, K. Chakrabarty, “Multisensor Data Fusion in Distributed Sensor Networks Using Mobile Agents,”Proceedings of 5th International Conf on Information Fusion, 6 pages, 2005.
B. Grocholslcy, J.F. Durrant-White, P. Gibbens, “An Information-Theoretic Approach to Decentralized Control of Multiple Autonomous Flight Vehicles,”The University of Sydney, 12 pages, 2000.
P. Ogren, E. Fiorelli, N.E. Leonard, “Cooperative Control of Mobile Sensor Networks; Adaptive Gradient Climbing in a Distributed Environment,”Automatic Control, IEEE Transactions, pp. 1292-1302, 2004.
N. Xiong, P. Svensson, “Multi-Sensor Management for Information Fusion: Issues and Approaches,”Information Fusion, vol. 3, pp. 163-186, 2002.
L.Y. Pao, N.T. Baltz, “Control of Sensor Information in Distributed Multisensor Systems,”American Control Conference, pp. 2397-2401, 1999.
M. Chu, H. Haussecker, F. Zhao, “Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks,”International Journal of High-Performance Computing Applications, 17 pages, 2002.
F. Zhao, J. Shin, J. Reich, “Information-Driven Dynamic Sensor Collaboration for Tracking Applications,”IEEE Signal Processing Magazine, 8 pages, 2002.
B. Horling, R. Mailler, M. Sims, V. Lesser, “Using and Maintaining Organization in a Large-Scale Sensor Network,”Proc. of Workshop on Autonomy, Delegation, and Control, U of Mass, 8 pages, 2003.
H. Wang, K. Yao, D. Estrin, “Information-theoretic Approaches for Sensor Selection and Placement in Sensor Networks for Target Localization and Tracking,”Journal of Communications and Networks, pp. 438-449, 2005.
M. Rabbat, R. Nowak, “Distributed Optimization in Sensor Networks,”Proceedings of the Third Intl. Symposium on Information Processing in Sensor Networks, 8 pages, 2004.
A. Savkin, R. Evans, E. Skafidas, “The Problem of Optimal Robust Sensor Scheduling,”paper—Australian Research Council and the Centre of Expertise in Networked Decision Systems, 6 pages, 2000.
S. Kullback and R. A. Leibler, “On Information and Sufficiency,”The Annals of Mathematical Statistics, pp. 79-86.
K. Kastella, “Discrimination Gain to Optimize Detection and Classification,”IEEE Transactions on Systems, Man, and Cybernetics, Par A: Systems and Humans7 pages, 1995.
S. Musick, K. Kastella, “Comparison of Sensor Management Strategies for Detection and Classification,”9th National Symposium on Sensor Fusion; 23 pages, Mar. 1996.
A. Willsky, M. Bello, D. Castanon, B. Levy, G. Verghese, “Combining and Updating of Local Estimates and Regional Maps Along Sets of One-Dimensional Tracks,”Automatic Control, IEEE Transaction, pp. 799-813, Aug. 1982.
T. H. Chung, V. Gupta, J.W. Burdick, R.M. Murray, “On a Decentralized Active Sensing Strategy Using Mobile Sensor Platforms in a Network,”Decision and Control, 6 pages, Dec. 2004.
A. Vailaya, M.A.T. Figueiredo, A.K. Jain, Z. Hong-Jiang Zhang, “Image Classification for Context-Based Indexing,”Image Processing, IEEE Transactions, pp. 117-130, Jan. 2001.
D. Koller, M. Sahami, “Hierarchically Classifying Documents Using Very Few Words,”Proc of the 14th Intl Conference on Machine Learning, 9 pages, 1997.
D.J.C. MacKay, “Bayesian Interpolation,”Neural Computation, 27 pages, May 1992.
U.S. Appl. No. 12/018,036, entitled “Information Processing System,” 28 pages, Jan. 22, 2008.
Tharmarasa et al., “Multitarget-Multisensor Management for Decentralized Sensor Networks,” SPIE, vol. 6236, pp. 1-11, 2006.
Schmaedeke, “Information based sensor management,” Paramax Systems Corporation, SPIE, vol. 1955, pp. 156-164, 1993.
McIntyre et al., “An Information Theoretic Approach to Sensor Scheduling,” Dept. of Electrical and Computer Engineering, SPIE vol. 2755, pp. 304-312, Apr. 1996.
Nash, “Optimal Allocation of Tracking Resources,” ORINCON Corporation, pp. 1177-1180, Dec. 1977.
Washburn et al., “Stochastic Dynamic Programming Based Approaches to Sensor Resource Management,” Fusion Technology and Systems Division, Alphatech, Inc., 8 pages, 1997.
Hashemipour et al., “Technical Notes and Correspondence,” IEEE Transactions on Automatic Control., vol. 33, No. 1, pp. 88-94, Jan. 1988.
Hintz et al., “Multi-Process Constrained Estimation,” IEEE, vol. 21, No. 1, pp. 237-244, Jan./Feb. 1991.
Hintz, “A Measure of the Information Gain Attributable to Cueing,” IEEE, vol. 21, No. 2, pp. 434-442, Mar./Apr. 1991.
Manyika et al., “An Information-theoretic Approach to Managem
Choe Howard C.
Guillochon James
Khosla Deepak
Baker & Botts L.L.P.
Barqadle Yasin
Fan Hua
Raytheon Company
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