A robust recurrent simultaneous perturbation stochastic approximation training algorithm for recurrent neural networks
Training of recurrent neural networks (RNNs) introduces considerable computational complexities due to the need for gradient evaluations. How to get fast convergence speed and low computational complexity remains a challenging and open topic. Besides, the transient response of learning process of RN...
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Main Authors: | , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/106964 http://hdl.handle.net/10220/17513 http://dx.doi.org/10.1007/s00521-013-1436-5 |
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Institution: | Nanyang Technological University |
Language: | English |