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20 M. Witbrock and M. Zagha, Backpropagation learning on the IBM GF 11", in Parallel Digital Implementation of Neural Networks, pp.77-104, 1993.
 

Summary: 20 M. Witbrock and M. Zagha, Backpropagation learning on the IBM GF 11", in Parallel Digital
Implementation of Neural Networks, pp.77-104, 1993.
21 H. Yoon and J.H. Nang Multilayer neural networks on distributed-memory multiprocessors",
Proceedings of International Neural Network Conference, Vol.2, pp.669-672, 1990.
22 S. Zeng, The Application of Parallel Processing Techniques to Neural Network Based Fingerprint
Recognition Systems", Thesis, Department of Electrical and Computer Engineering, West Virginia
University, 1994.
23 X. Zhang, M. Mckenna, J.F. Mesirov and D. Waltz, An e cient implementation of the backpro-
pogation algorithm on the Connection Machine CM-2", in Parallel Computing, Vol.14, pp.317-327,
1990.
20
4 E.M. Deprit, Implementing recurrent back-propagation on the Connection Machine", in Neural
Networks, Vol.2, pp.295-314, 1989.
5 F. Distante, M. Sami, R. Stefanelli and G. Storti-Gajani, Mapping neural nets onto a massively
parallel architecture: a defect-tolerance solution", in Proceedings of The IEEE, Vol.79, pp.444-460,
October 1991.
6 S.K. Foo, P. Saratchandran and N. Sundararajan, Analysis of training set parallelism for back-
propagation neural networks", in International Journal of Neural Systems, Vol.6, pp.61-78, 1995.
7 Y. Fujimoto, N. Fukuda and T. Alcabane, Massively parallel architectures for large scale neural
network simulations", in IEEE Transactions on Neural Networks, Vol.3, pp.876-888, November

  

Source: Ammar, Hany H. - Department of Computer Science and Electrical Engineering, West Virginia University

 

Collections: Computer Technologies and Information Sciences