Autoencoders (Ordinary type)
the Algorithm returns a fully trained autoencoder based ELM, you can use it to train a deep network by changing the original feature representations,it code or decode any input simple depending on the training parameters (input and output weights ) .
please cite as :
B. Tarek, H. Mouss, O. Kadri, L. Saïdi, and M. Benbouzid, “Aircraft Engines Remaining Useful Life Prediction using an Improved Online Sequential Extreme Learning Machine,” Appl. Sci., 2020.
In this link an example of regenerating of an image from the encoded matrix using an autoencoder is illustrated:
https://www.youtube.com/watch?v=ZdyUnbbSdN8&feature=youtu.be
Citation pour cette source
B. Tarek, H. Mouss, O. Kadri, L. Saïdi, and M. Benbouzid, “Aircraft Engines Remaining Useful Life Prediction using an Improved Online Sequential Extreme Learning Machine,” Appl. Sci., 2020.
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AE_ELM
Version | Publié le | Notes de version | |
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1.6 | description |
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1.5 | citation is add |
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1.4 | new version |
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1.3 | new version with improvement, to make easy to undrestand from the newcomers To autoencoders |
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1.2 | new features |
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1.1 | image |
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1.0 |
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