Data processing: measuring – calibrating – or testing – Testing system – Of circuit
Reexamination Certificate
2006-04-25
2006-04-25
Bui, Bryan (Department: 2863)
Data processing: measuring, calibrating, or testing
Testing system
Of circuit
C702S188000, C706S045000
Reexamination Certificate
active
07035754
ABSTRACT:
A system for determining accurate solutions for object classification problems is provided. The system is generally for identifying an object, wherein the object is represented by a signal. The system includes a computer system, a training information data set, a labeler, a reduct calculator a testing information data set and a reduct classification fuser.
REFERENCES:
patent: 5701400 (1997-12-01), Amado
patent: 5970171 (1999-10-01), Baraghimian et al.
patent: 6393413 (2002-05-01), Jorgensen et al.
J. A. Starzyk, Dong Liu, Zhi-Hong Liu, D. Nelson, J. Rutkowski, “Entropy-based optimum test points selection for analog fault dictionary techniques, ” IEEE Transactions on Instrumentation and Measurement, vol. 53, No. 3, Jun. 2004, pp. 754-761.
D. E. Nelson, J. A. Starzyk, and D. D. Ensley, “Iterated wavelet transformation and signal discrimination for HRR radar target recognition”, IEEE Trans. on Systems, Man and Cybernetics, Part A, vol. 33, No. 1, Jan. 2003, pp. 52-57.
D. E. Nelson, J. A. Starzyk, and D. D. Ensley, “Iterative Wavelet Transformation and Signal Discrimination for HRR Radar Target Recognition,” Multidimensional Systems and Signal Processing, vol. 14, No. 2, 2002.
J. A. Starzyk, D. E. Nelson, and K. Sturtz, “A Mathematical Foundation for Improved Reduct Generation in Information Systems”, Journal of Knowledge and Information Systems, v. 2 n. 2, Mar. 2000 p. 131-146.
J. A. Starzyk, D. E. Nelson, and K. Sturtz, “Reduct Generation in Information Systems”, Bulletin of International Rough Set Society, 1999, 3 (1/2).
D. E. Nelson and J.A. Starzyk, “High Range Resolution Radar Signal Classification: A Partitioned Rough Set Approach” Proc. Southeastern Symposium on System Theory, (Athens, OH, 2001).
D.E. Nelson and J. A. Starzyk, “High Range Resolution Radar—Extensions to Rough Set Theory for Automatic Target Recognition”, SPIE 15th Annual Int. Symp. on Aerospace/Defense Sensing Simulation and Controls, (Orlando FL, Apr. 2001) Best Paper award.
D. E. Nelson and J. A Starzyk “Fusing Marginal Reducts for HRR Target Identification” 4th World Multi-Conference on Systems, Cybernetics and Informatics (SC12000), (Orlando, Florida, Jul. 2000), pp. 452-460 Best Paper award.
J. A. Starzyk, D. E. Nelson, and K. Sturtz, “Reduct Generation in Information Systems”, The Sixth Int. Workshop on Rough Sets, Data Mining and Granular Computing, at JCIS'98, (Research Triangle Park, NC), Oct. 1998.
D. E. Nelson end J. A. Starzyk, “Advanced Feature Selection Methodology for Automatic Target Recognition”, Proc. Southeastern Symposium on System Theory, (Coolville, TN, 1997).
J. A. Starzyk and D. Nelson, “Independent Classifiers in Ontogenic Neural Networks for ATR”, Adaptive Distributed Parallel Computing Symposium (Fairborn, OH, 1996).
Dissertation entitled “High Range Resolution Radar Target Classification: A Rough Set Approach” by Nelson, Jun. 2001.
Publication—Articles in Professional Journals, www. ent.ohiou.edu/˜starzyk
etwork/Resarch/papers.htm, Printed Apr. 13, 2005.
Nelson Dale E.
Starzyk Janusz A.
Bui Bryan
Calfee Halter & Griswold LLP
Ohio University
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