Robust neural training and pruning algorithms for a class of nonlinear tracking control systems
This thesis focuses on developing robust online training and pruning algorithms for a class of neural network tracking control systems. In particular, a complete convergence analysis is presented for all the algorithms with different learning schemes, respectively.
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Format: | Thesis |
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2008
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Online Access: | https://hdl.handle.net/10356/4973 |