A neural network pruning algorithm with embedded gradient-conjugate training for the identification of large flexible space structures

Author Info

Xiao-Hua Yu, University of California - IrvineFollow

Recommended Citation

Published in Proceedings of the 1998 IEEE International Conference on Control Applications, Volume 1, September 1, 1998, pages 293-297.

NOTE: At the time of publication, the author Xiao-Hua Yu was not yet affiliated with Cal Poly.

The definitive version is available at https://doi.org/10.1109/CCA.1998.728427.

Abstract

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 real-time 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 dramatically reduce the size of neural network while maintaining compatible identification accuracy.

Disciplines

Electrical and Computer Engineering

Copyright

1998 IEEE.

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