A Sparse Auto Encoder Deep Process Neural Network Model and its Application
Aiming at the problem of time-varying signal pattern classification, a sparse auto-encoder deep process neural network (SAE-DPNN) is proposed. The input of SAE-DPNN is time-varying process signal and the output is pattern category. It combines the time-varying signal classification method of process...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Atlantis Press
2017-01-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/25881240/view |