File Exchange

image thumbnail

Denoising autoencoders

version 1.4.0 (640 KB) by BERGHOUT Tarek
In this code a full version of denoising autoencoder is presented.


Updated 15 Apr 2019

View License

An autoencoder is a type of artificial neural network used to learn efficient data (codings) in an unsupervised manner. The aim of an auto encoder is to learn a representation (encoding) for a set of data,
denoising autoencoders is typically a type of autoencoders that trained to ignore “noise’’ in corrupted input samples.
In this code we represent to you a denoising autoencoder with a single hidden layer feed forward networks trained by Extreme learning machine.
This algorithm allows training and testing of any dataset with the user defined parameters and shows the main results of both of them.

in this version noise is added randomly by frames(blocks of data) , if you need any information or help concerning your deep learning projects contact me via:
the referances that i used to create the code are available in this link:

Cite As

BERGHOUT Tarek (2019). Denoising autoencoders (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (2)

Thanks it is quite helpful


thanks a lot for sharing



some coments are added


a new version that trains an autoencoders by adding random samples of noise in each frame (block of data) .


new version


a new illustration image is description notes Note were added

MATLAB Release Compatibility
Created with R2013b
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired by: Autoencoders

Discover Live Editor

Create scripts with code, output, and formatted text in a single executable document.

Learn About Live Editor