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Transformer fault diagnosis using continuous sparse autoencoder
This paper proposes a novel continuous sparse autoencoder (CSAE) which can be used in unsupervised feature learning. The CSAE adds Gaussian stochastic unit into activation function to extract features of nonlinear data. In this paper, CSAE is applied to solve the problem of transformer fault recogni...
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| Publicado no: | Springerplus |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer International Publishing
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4830783/ https://ncbi.nlm.nih.gov/pubmed/27119052 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s40064-016-2107-7 |
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