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Multi-label spacecraft electrical signal classification method based on DBN and random forest

Fig 3

The topology of the SAE network.

The representation ability of only auto-encoder is too limited. Thus the stacked auto-encoder composed of multiple auto-encoder is able to greatly improve the representational power. The activation value of one auto-encoder is the input of the upper auto-encoder. It can be used as a pre-training technique and it should belong to the unsupervised learning method for it doesn’t need label information at all. The topological graph of the SAE is shown in Fig 3.

Fig 3

doi: https://doi.org/10.1371/journal.pone.0176614.g003