Autoencoders (Ordinary type)

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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.

Remerciements

Inspiré par : Run Length coding

A inspiré : Denoising Autoencoder

Catégories

En savoir plus sur Statistics and Machine Learning Toolbox dans Help Center et MATLAB Answers

Informations générales

Compatibilité avec les versions de MATLAB

  • Compatible avec toutes les versions

Plateformes compatibles

  • Windows
  • macOS
  • Linux
Version Publié le Notes de version Action
1.6

description

1.5

citation is add

1.4

new version

1.3

new version with improvement, to make easy to undrestand from the newcomers To autoencoders

1.2

new features

1.1

image

1.0