George Rudolph
Assistant Professor of
Computer Science, The Citadel 225 Thompson Hall
Department of Mathematics and Computer
Science, The Citadel
171 Moultrie Street, Charleston, SC 29409
Phone: 843-573-2172, Fax:
843-953-7391, Email: George.rudolph@citadel.edu
Ph.D. in Computer Science, 1995, Brigham Young University, Dissertation: Location-Independent Neural Network Models
M.S. in Computer Science, 1991, Brigham Young University
B.S. in Computer Science, 1989, Brigham Young University
Rudolph, G.L. Anatomy of a Design, Revisited, Journal of Combinatorial Mathematics and Combinatorial Computing, submitted, 2009.
Francel M., Hurd, S., Rudolph, G., Sarvate, D. The Anatomy of a Design, Congressus Numerantium 181, pp. 77-88, 2006.
Rudolph, G.L., Martinez, T.R. A Transformation Strategy for Implementing Distributed Multilayer Feedforward Networks: Backpropagation Transformation, Future Generation Computer Systems, vol. 12, pp. 547-564. Elsevier Science, B.V. 1997.
Rudolph, George L., and Tony R. Martinez. LIA: A Location-Independent Transformation for ASOCS Adaptive Algorithm 2 ,International Journal of Neural Systems, vol. 7, no. 5, pp. 639-653, 1996.
Rudolph, George L., and Tony R. Martinez. An Efficient Transformation for Implementing Two-layer Feedforward Neural Networks. Journal of Artificial Neural Networks, vol. 2, no. 3, pp. 263-282, 1995.
Rudolph, George L., and Tony R. Martinez. A Transformation for Implementing Localist Neural Networks. In Neural Parallel and Scientific Computations, vol. 3, no. 2, pp. 173-188, 1995.
Rudolph, George L., and Tony R. Martinez. Location-Independent Transformations: A General Strategy for Implementing Neural Networks, In International Journal on Artificial Intelligence Tools, vol. 3, No. 3, pp. 417-427, 1994.
Rudolph, George L., and Tony R. Martinez. A Transformation for Implementing Efficient Dynamic Backpropagation Neural Networks. In Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pp. 41-44, 1995.
Rudolph, George L., and Tony R. Martinez. A Transformation for Implementing Neural Networks with Localist Properties. In Intelligent Systems. E. A. Yfantis (ed.), Vol. 1, pp. 637-645, Kluwer Academic Publishers, 1995.
Stout, Matthew, Linton Salmon, George Rudolph, and Tony R. Martinez. A Multi-Chip Module Implementation of a Neural Network. In Proceedings of the IEEE Multi-Chip Module Conference MCMC-94, pp. 20-25, 1994.
Stout, Matthew, George Rudolph, Tony R. Martinez, and Linton Salmon. A VLSI Implementation of a Parallel Self-Organizing Learning Model. In Proceedings of the 12th International Conference on Pattern Recognition, vol. 3, pp. 373-376, 1994.
Martinez, Tony R., and George Rudolph. A Learning Model for Adaptive Network Routing. In Proceedings of the International Workshop on Applications of Neural Networks to Telecommunications IWANNT93, pp. 183-187, 1993.
Rudolph, George L., and Tony R. Martinez. An Efficient Static Topology for Modeling ASOCS. International Conference on Artificial Neural Networks. In Artificial Neural Networks, Kohonen, et. al. (eds), Elsevier Science Publishers, pp. 729-734, 1991.
Rudolph, George L., and Tony R. Martinez. DNA: A New ASOCS Model With Improved Implementation Potential. In Proceedings of the IASTED International Symposium on Expert Systems and Neural Networks, pp. 12-15, 1989.
Campbell, D., G. Rudolph. A Polynomial Time Algorithm for Extended 2Sat. Proceedings, Western Educational Computing Conference, pp. 151-155. Western Periodicals Company, North Hollywood, CA. 1989.
G. Rudolph. Some Guidelines For Deciding Whether To Use A Rules Engine. JESS mail archives at http://www.mail-archive.com/jess-users@sandia.gov/msg01887.html, 2000.