Autoencoders (Ordinary type)

Ahora está siguiendo esta publicación

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

Citar como

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.

Agradecimientos

Inspirado por: Run Length coding

Inspiración para: Denoising Autoencoder

Categorías

Más información sobre Statistics and Machine Learning Toolbox en Help Center y MATLAB Answers.

Información general

Compatibilidad con la versión de MATLAB

  • Compatible con cualquier versión

Compatibilidad con las plataformas

  • Windows
  • macOS
  • Linux
Versión Publicado Notas de la versión 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