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F
K. Carr, Cannava, K., Pescatore, R., Georgiopoulos, M., and Anagnostopoulos, G., “Fast Stable and on-line training of Fuzzy ARTMAP using a novel, conservative, slow learning strategy”, in ANNIE 2004 conference, St. Louis, MI, 2004.
K. Carr, Cannava, K., Pescatore, R., Georgiopoulos, M., and Anagnostopoulos, G. C., “Fast Stable and on-line training of Fuzzy ARTMAP using a novel,conservative,slow learning strategy”, Neural Networks, pp. 63–69, 2004.
A. Henninger, Gonzalez, A., Gerber, W., Georgiopoulos, M., and DeMara, R., “On the Fidelity of SAFs: Can performance data help?”, Proceedings of the 2000 Interservice/Industry Training,Simulation and Education Conference (I/ITSEC-2000), pp. 147–154, 2000.
G. Bebis, Deaconu, T., and Georgiopoulos, M., “Fingerprint identification using Delaunay triangulation”, IEEE International Conference on Information,Intelligence and Systems, pp. 452–459, 1999.
D. Charalampidis, Anagnostopoulos, G. C., Georgiopoulos, M., and Kasparis, T., “Fuzzy ART and ARTMAP with adaptive weighted distances”, Proceedings of SPIE,Conference on Applications and Science of Computational Intelligence V, vol. 4739, pp. 86–97, 2002.
J. Huang, Georgiopoulos, M., and Heileman, G. L., “Fuzzy ART properties”, Neural Networks, vol. 8, pp. 203-213, 1995.
D. Charalampidis, Kasparis, T., Georgiopoulos, M., and Rolland, J., “A Fuzzy ARTMAP based classification of natural textures”, Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society, pp. 507–511, 1999.
I. Dagher, Georgiopoulos, M., Heileman, G., and Bebis, G., “Fuzzy ARTVar: An Improved Fuzzy ARTMAP Algorithm”, International Joint Conference on Neural Networks, pp. 1688–1693, 1998.
C. Sentelle, Hong, S. L., Anagnostopoulos, G. C., and Georgiopoulos, M., “A fuzzy gap statistic for Fuzzy C-Means”, Proceedings of the 11th IASTED International Conference on Artificial, 2007.
C. Sentelle, Hong, S. L., Georgiopoulos, M., and Anagnostopoulos, G. C., “A Fuzzy Gap-statistic for Fuzzy C-Means”, in The 11th IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2007), Palma de Malorca, Spain, 2007.
N. Shorter and Kasparis, T., “Fuzzy SART Clustering for 3D Reconstruction from Irregular LIDAR Data”, vol. 2.8, pp. 1122 – 1129, 2006.
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M. Zhong, Coggeshall, D., Ghaneie, E. G., Pope, T., Rivera, M. A., Georgiopoulos, M., and Anagnostopoulos, G. C., “Gap-Based Estimation: Choosing the smoothing parameters for Probabilistic and General Regression Neural Networks”, in WCCI 2006, Vancouver, Canada, 2006.
M. Zhong, Coggeshall, D., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Gap-Based Estimation: Choosing the Smoothing Parameters for Probabilistic and General Regression Neural Networks”, Proceedings of the 2006 IEEE-INNS-ENNS International Joint Conference on Neural Networks, pp. 1870–1877, 2006.
G. L. Heileman, Georgiopoulos, M., and Roome, W. D., “A general framework for concurrent simulation on neural network models”, in International Joint Conference on Neural Networks (IJCNN), Baltimore, MD, 1992.
G. L. Heileman, Georgiopoulos, M., and Roome, W. D., “A general framework for concurrent simulation on neural network models”, IEEE Transactions on Software Engineering, vol. 18, pp. 551-562, 1992.
M. Georgiopoulos, Dagher, I., Heileman, G. L., and Bebis, G., “The generalization capabilities of ARTMAP”, in International Conference on Neural Networks, Houston, TX, 1997.
M. Zhong, Georgiopoulos, M., Anagnostopoulos, G. C., and Mollaghasemi, M., “Generalized Entropy for Splitting Numerical Attributes in Decision Tree Classifiers”, Proceedings of the 19th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (FLAIRS 2006), pp. 604–609, 2006.
J. Reeder and Georgiopoulos, M., “Generative Neural Networks for Multi-Task Life-Long Learning”, The Computer Journal, vol. 57, no. 3, pp. 427-450, 2014.
A. Kaylani, Al-Daraiseh, A., Georgiopoulos, M., Mollaghasemi, M., Anagnostopoulos, G. C., and Wu, A. S., “Genetic Optimization of ART Neural Network Architectures”, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2007), pp. 379–384, 2007.
G. Bebis, Uthiram, S., and Georgiopoulos, M., “Genetic Search for Face Detection and Verification”, IEEE International Conference on Information,Intelligence and Systems, pp. 360–367, 1999.
A. Al-Daraiseh, Kaylani, A., Georgiopoulos, M., Mollaghasemi, M., Anagnostopoulos, G. C., and Kaburlasos, V. G., “Genetically Engineered ART Architectures”, Heidelberg: Springer-Verlag,in Computational Intelligence Based on Lattice Theory,Studies in Computational Intelligence, vol. 67, pp. 233–262, 2007.
R. Miguez, Georgiopoulos, M., and Kaylani, A., “A Genetically Engineered Probabilistic Neural Network”, Nonlinear Analysis: Theory, Methods & Applications, vol. 73, pp. 1783-1791, 2010.
A. Al-Dairaseh, Georgiopoulos, M., Wu, A. S., Anagnostopoulos, G., and Mollaghasemi, M., “GFAM: A genetic algorithm optimization of Fuzzy ARTMAP”, in WCCI 2006 (Fuzzy Systems), Vancouver, Canada, 2006.
A. Al-Dairaiseh, Kaylani, A., Georgiopoulos, M., Mollaghasemi, M., Wu, A. S., and Anagnostopoulos, G., “GFAM Evolving Fuzzy ARTMAP Neural Networks”, Neural Networks journal, vol. 20, pp. 874-892, 2007.
A. Al-Daraiseh, Kaylani, A., Georgiopoulos, M., Wu, A. S., Mollaghasemi, M., and Anagnostopoulos, G. C., “GFAM:Evolving Fuzzy ARTMAP Neural Networks”, vol. 20.8, pp. 874–892, 2007.
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C. S. Ho, Liou, J. J., Georgiopoulos, M., and Christodoulou, C., “Hardware implementation of an adaptive resonance theory (ART) neural network using compensated amplifiers”, in Proceedings SPIE, Orlando, FL, 1994.
C. S. Ho, Liou, J. J., and Georgiopoulos, M., “Hardware implementation of ART1 memories using a mixed analogdigital approach”, in IEEE World Congress on Computational Intelligence, Orlando, Fl, 1994.
G. Rabadi, Anagnostopoulos, G. C., and Mollaghasemi, M., “A heuristic algorithm for the just-in-time single machine scheduling problem with setups: A comparison with simulated annealing”, vol. 32, pp. 326–335, 2007.
S. Verzi, Heileman, G., Georgiopoulos, M., and Healy, M., “Hierarchical ARTMAP”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 41–46, 2008.
J. Reeder, Georgiopoulos, M., Castro, J., Burns, S., Anagnostopoulos, G., and Mollaghasemi, M., “Hilbert Space Filling Curve Nearest Neighbor”, in The ISAS and CITSA 2005, Orlando, FL, 2005.
G. C. Anagnostopoulos and Georgiopoulos, M., “Hypershere ART and ARTMAP for unsupervised and supervised incremental learning”, in the International Joint Conference on Neural Networks, Como, Italy, 2000.
G. C. Anagnostopoulos and Georgiopoulos, M., “Hypersphere ART and ARTMAP for Unsupervised and Supervised,Incremental Learning”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 59–64, 2000.
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C. Puklavage, Pirela, A., Gonzalez, A. J., and Georgiopoulos, M., “Imitating personalized expressions through an Avatar using Machine Learning”, in Proceedings of the 23rd International FLAIRS conference, 2010.
G. Bebis and Georgiopoulos, M., “Improving generalization by using genetic algorithms to determine the neural network size”, in Southcon 95, 1995.
M. J. Johnson, Georgiopoulos, M., Mollaghasemi, M., and McGinnis, M., “Improving human behavior in simulations – OneSAF tested baseline intelligent computer generated objects”, in SCS, Military, Government and Aerospace Simulation Symposium 2001 (MGA 2001) Conference, Seattle, Washington, 2001.
C. Young, Georgiopoulos, M., Hagen, S., Geiger, C., Dagley-Falls, M., Islas, A., Ramsey, P., Lancey, P., Forde, D., and Bradbury, E., “Improving Student Learning in Calculus through Applications”, International Journal of Mathematical Education in Science and Technology, vol. 42, pp. 591-604, 2011.
G. Bebis, Papadourakis, G. M., Georgiopoulos, M., and Heileman, G. L., “Increasing classification accuracy using multiple-neural-network schemes”, in Proceedings of the 1992 SPIE Conference (Technical Program on Intelligent Information Systems), Orlando, FL, 1992.
G. Bebis, Georgiopoulos, M., Shah, M., and da Lobo, V. N., “Indexing Based on Algebraic Functions of Views”, Computer Vision and Image Understanding, vol. 72.3, pp. 360–378, 1998.
M. Dagley-Falls, Georgiopoulos, M., and Young, C., “Influencing sense of community in a STEM living-learning community: An NSF STEP funded project”, in Proceedings of the 2010 ASEE Conference and Exposition, 2010.
H. Bahr, Georgiopoulos, M., and DeMara, R., “Integer-encoded massively parallel processing of fast learning Fuzzy ARTMAP neural networks”, in Proceedings SPIE; Conference of Applications and Science of Artificial Neural Networks III, Orlando, FL, 1997.
J. Reeder, Gita, S., Georgiopoulos, M., and Anagnostopoulos, G. C., “Intelligent Trading Agents for Massively Multi-player Game Economies”, Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference, pp. 102–107, 2008.
J. Reeder, Miguez, R., Sparks, J., Georgiopoulos, M., and Anagnostopoulos, G. C., “Interactively Evolved Modular Neural Networks for Game Agent Control”, IEEE Symposium on Computational Intelligence and Games (CIG 08, pp. 167–174, 2008.
L. Massi, Georgiopoulos, M., Young, C. Y., Ford, C. M., Lancey, P., Bhati, D., and Small, K. A., “Internships and Undergraduate Research: Impact, Support, and Institutionalization of an NSF S-STEM Program through Partnerships with Industry and Funding from Federal and Local Workforce Agencies”, Proceedings of the 120th ASEE Conference and Exposition. Atlanta, GA, June 23-26, 2013.
K
M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “A k -norm pruning algorithm for decision tree classifiers based on error rate estimation”, Machine Learning, vol. 71, pp. 55-88, 2008.
C.Li, M. Georgiopoulos, R. DeMara,, and G.C. Anagnostopoulos, M. Georgiopoulos, “Kernel Principal Subspace Mahalanobis Distances for Outlier Detection”, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA, 2011.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Kernel-based Distance Metric Learning in the Output Space”, in International Joint Conference on Neural Networks (IJCNN), Dallas, TX, August 04-09, 2013.
M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “k-Norm Misclassification Rate Estimation for Decision Trees”, Proceedings of the 11th IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2007), pp. 163–168, 2007.
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G. Bebis, Georgiopoulos, M., da Lobo, V. N., and Shah, M., “Learning affine transformations”, Pattern Recognition, vol. 32.10, pp. 1783–1799, 1999.
G. Bebis, Georgiopoulos, M., da Lobo, V. N., and Shah, M., “Learning affine transformations of the plane for model-based object recognition”, in 13th International Conference on Pattern Recognition (ICPR-96), Vienna, Austria, 1996.
G. Bebis, Georgiopoulos, M., and da Lobo, V. N., “Learning geometric hashing functions for model-based object recognition”, in Fifth International Conference on Computer Vision, ICCV-1995, Cambridge, MA, 1995.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, vol. 68, pp. 361-384, 2011.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, in the 25th International Symposium on Computer and Information Sciences, London, UK, 2010.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, 2010.
G. Bebis, Georgiopoulos, M., and Bhatia, S., “Learning orthographic transformations for object recognition”, in 1997 IEEE International Conference on Systems, Man, and Cybernetics, Orlando, FL, 1997.
H. K. Fernlund, Gonzalez, A. J., Georgiopoulos, M., and DeMara, R., “Learning tactical human behavior through observation of human performance”, Cybernetics–Part B: Cybernetics,Man,IEEE Transactions on Systems, vol. 36.1, pp. 128–140, 2006.
A. Henninger, Gonzalez, A., Georgiopoulos, M., and DeMara, R., “The Limitations of Static Performance Metrics for Dynamic Tasks Learned Through Observation”, Proceedings of the Tenth Conference on Computer Generated Forces and Behavioral Representation, pp. 147–154, 2001.
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M. J. Johnson, Mollaghasemi, M., Georgiopoulos, M., and McGinnis, M., “A methodology for human behavior modeling in computer generated forces”, in Industrial Engineering Research Conference 2001 (IERC 2001), Dallas, TX, 2001.
J. Secretan, Georgiopoulos, M., Maidhof, I., Shibly, P., and Hecker, J., “Methods for Parallelizing the Probabilistic Neural Network on a Beowulf Cluster Computer”, 2006.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G. C., “M-GFAM:An Elegant Approach to Genetically Optimize Fuzzy ARTMAP Neural Network Architectures”, Proceedings of the 8th International Conference on Natural Computing (ICNC 2007),part of the 10th Joint Conference on Information Sciences (JCIS 2007), pp. 1617-1623, 2007.
A. Henninger, Gonzalez, A., Georgiopoulos, M., and DeMara, R., “Modeling Semi-Automated Forces with Neural Networks: Performance Improvement through a Modular Approach”, 2000.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: An adaptive multi-objective approach to evolving ART architectures”, IEEE Transactions on Neural Networks, vol. 21, pp. 529-550, 2010.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: An adaptive multi-objective approach to evolving ART architectures”, IEEE Transactions on Neural Networks, vol. 21, pp. 529-550, 2010.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: Multi-Objective Optimization of ART Architectures”, in 2008 IEEE Congress on Evolutionary Computation (IEEE CEC 2008), Hong Kong, 2008.
X. Rui, Anagnostopoulos, G. C., and II, W. D., “Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 4., pp. 65–77, 2007.
T.Rubio, Zhang, T., Georgiopoulos, M., and Kaylani, A., “Multi-Objective Evolutionary Optimization of Exemplar-Based Classifiers: A PNN Test Case”, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA, 2011.
T. Zhang, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Multi-Objective Model Selection via Racing”, IEEE Transactions on Cybernetics, vol. 46, no. 8, pp. 1863-1876, 2015.
E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Multiple mobile user tracking with neural network-based adaptive array antennas”, SPIE Conference on Digital Wireless Communications, pp. 88–97, 1999.
C. Christodoulou, Georgiopoulos, M., and Zooghby, E. A., “Multiple Source Angle of Arrival Estimation using Neural-Network-based Smart Antennas”, Proceedings SPIE; Conference on Digital Wireless Communications II, pp. 94–99, 2000.
E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Multiple sources neural network direction finding with arbitrary separations”, IEEE-APS Conference on Antennas and Propagation for Wireless Communications, pp. 57–60, 1998.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Multi-Task Classification Hypothesis Space with Improved Generalization Bounds ”, IEEE Transactions on Neural Networks and Learning Systems, vol. accepted for publication (acceptance was communicated in July 2014), 2014.
C. Li, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Multi-Task Classification Hypothesis Space with Improved Generalization Bounds”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 7, pp. 1468-1479, 2015.
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A. E. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Neural network approach for direction of arrival estimation”, in Proceedings SPIE; Conference of Applications and Science of, Orlando, FL, 1997.
G. L. Heileman, Papadourakis, G. M., and Georgiopoulos, M., “A neural network associative memory for real-time applications”, Neural Computation, vol. 2, pp. 107-115, 1990.
E. A. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Neural Network based beamforming for interference cancellation”, Conference on Applications and Science of Computational Intelligence, pp. 420–429, 1998.
C. G. Christodoulou, Zooghby, E. A. H., and Georgiopoulos, M., “Neural network processing for adaptive array antennas”, IEEE Antennas and Propagation Society International Symposium, pp. 2584–2587, 1999.
E. A. H. Zooghby, Christodoulou, C., and Georgiopoulos, M., “Neural Network-Based Adaptive Beamforming for One- and Two-Dimensional Antenna Arrays”, IEEE Transactions on Antennas and Propagation, vol. 46.1, pp. 1891–1893, 1998.
A. H. E. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Neural network-based adaptive beamforming for one- and two-dimensional antenna arrays”, IEEE Transactions on Antennas and Propagation, vol. 46, pp. 1891-1893, 1998.
A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “A Neural Network-Based Smart Antenna for Multiple Source Tracking”, IEEE Transactions on Antennas and Propagation, vol. 48.5, pp. 768–776, 2000.
E. A. H. Zooghby, Christodoulou, C., and Georgiopoulos, M., “A neural-network-based linearly constrained minimum variance beamformer”, Microwave and Optical Technology Letters, vol. 21.6, pp. 451–455, 1999.
G. C. Anagnostopoulos and Georgiopoulos, M., “New Geometrical Concepts in Fuzzy-ART and Fuzzy-ARTMAP: Category Regions”, IEEE-INNS International Joint Conference on Neural Networks (IJCNN 2001), pp. 32–37, 2001.
G. C. Anagnostopoulos and Georgiopoulos, M., “New geometrical perspective of fuzzy ART and fuzzy ARTMAP learning”, Proceedings of SPIE; Conference on Applications and Science of Computational Intelligence IV, pp. 22–32, 2001.
M. Georgiopoulos, Heileman, G. L., and J. Huang, “The N-N-N conjecture in ART1”, Neural Networks, vol. 5, pp. 745-753, 1992.
M. Georgiopoulos, Heileman, G. L., and Huang, J., “The N-N-N conjecture in ART1 Conference”, in International Joint Conference on Neural Networks (IJCNN), Baltimore, MD, 1992.
A. Koufakou, Secretan, J., and Georgiopoulos, M., “Non-derivable itemsets for fast outlier detection in large high dimensional categorical data”, Knowledge and Information Systems, pp. 1-29, 2010.
T. Kasparis, Georgiopoulos, M., and Payne, E., “Non-linear filtering techniques for narrow-band interference rejection in direct sequence spread-spectrum systems”, in MILCOM 91, McLean, Virginia, 1991.
A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “A novel approach to adaptive nulling with neural networks”, Southeastcon, pp. 216–219, 1998.
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S. Verzi, Heileman, G. L., Georgiopoulos, M., and Anagnostopoulos, G. C., “Off-line structural risk minimization and BARTMAP-S”, in the 2002 International Joint Conference on Neural Networks, Honolulu, Hawaii, 2002.
S. Verzi, Heileman, G., Georgiopoulos, M., and Anagnostopoulos, G. C., “Off-line structural risk minimization and BARTMAP-S”, Neural Networks, pp. 2533–2538, 2002.
A. Vartak, Georgiopoulos, M., and Anagnostopoulos, G. C., “On-line Gaussae Newton-based learning for fully recurrent neural networks”, Nonlinear Analysis, vol. 63, pp. e867–e876, 2005.
T. Zhang, Georgiopoulos, M., and Anagnostopoulos, G. C., “Online Model Racing Based on Extreme Performance”, in GECCO 2014, Vancouver, Canada, July 12-16, 2014, accepted for publication, 2014.
G. Bebis and Georgiopoulos, M., “Optimal feed-forward neural network architectures”, IEEE Potentials, pp. 27-31, 1994.
M. Georgiopoulos, Fernlund, H., Bebis, G., and Heileman, G. L., “Order of Search in Fuzzy ART and Fuzzy ARTMAP: A geometrical interpretation”, in International Conference on Neural Networks (ICNN 1996), Washington, DC, 1996.
M. Georgiopoulos, Fernlund, H., Bebis, G., and Heileman, G., “Order of Search in Fuzzy ART and Fuzzy ARTMAP: Effect of the Choice Parameter”, Neural Networks, vol. 9.9, pp. 1541-1559, 1996.
I. Dagher, Georgiopoulos, M., Heileman, G. L., and Bebis, G., “Ordered fuzzy ARTMAP: a fuzzy ARTMAP algorithm with a fixed order of pattern presentation”, IEEE International Joint Conference on Neural Networks, pp. 1717–1722, 1998.
H. G. L. I. Dagher, M. Georgiopoulos, “An Ordering Algorithm for Pattern Presentation in Fuzzy ARTMAP That Tends to Improve Generalization Performance”, IEEE Transactions on Neural Networks, vol. 10.4, pp. 768–778, 1999.
M. Georgiopoulos, Koufakou, A., Anagnostopoulos, G. C., and Kasparis, T., “Over-training in Fuzzy ARTMAP: Myth or Reality?”, Proceedings of the International Joint Conference on Neural Networks, pp. 1186–1190, 2001.
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M. Georgiopoulos, “Packet error probabilities in direct sequence spread spectrum packet radio networks”, IEEE Trans. on Comm., vol. 38, pp. 1599-1606, 1990.
M. Georgiopoulos, “Packet error probabilities in direct sequence spread spectrum packet radio networks with BCH codes”, in MILCOM 88, San Diego, California, 1988.
M. Georgiopoulos, “Packet error probabilities in frequency hopped spread spectrum packet radio networks–Memoryless frequency hopping patterns considered”, IEEE Trans. on Comm., vol. 36, pp. 720-724, 1988.
M. Georgiopoulos, “Packet error probabilities in frequency hopped spread spectrum packet radio networks–Memoryless frequency hopping patterns considered”, in the 26th IEEE Conference on Decision and Control, Los Angeles, California, 1987.

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