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Proceedings of the 1998 IEEE International Conference on Control Applications (Cat. No.98CH36104)
The choice of network dimension is a fundamental issue in the design of artificial neural networks. A larger neural network is powerful for solving problems while a smaller neural network is always advantageous in realtime environment where speed is crucial. In this paper, a network pruning algorithm with embedded gradient-conjugate training is investigated and applied to the identification of a large flexible space structure. Computer simulation results show that this approach can dramaticallydoi:10.1109/cca.1998.728427 fatcat:4kgrtxs3m5hg7akvtyvy2fzbya