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BERGHOUT Tarek


Last seen: 2 giorni ago

University of batna-2 Algeria

77 total contributions since 2018

Tarek BERGHOUT was born in 1991 in RAHBAT-Algeria, he studied in BATNA university (Algeria), he has a Master degree in industrial engineering and manufacturing (2015).
Currently he is a Freelance Researcher and codes writer specialized in industrial prognosis based on Machine Learning tools.
interests :
- Extreme Learning Machine.
- Dynamic data compression with Deep ANNs.
- Data-driven prediction based Deep ANNs.
- Time varying data challenges.
- Linear Approximation and dynamic programming.
- Big data and Deep Learning.
hobbies: gardening, photography, Photoshop designing
email: berghouttarek@gmail.com

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Contributions in
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Submitted


Aircraft Engines Remaining Useful Life Prediction
Aircraft Engines Remaining Useful Life Prediction with an Improved Online Sequential Extreme Learning Machine

11 giorni ago | 14 downloads |

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Submitted


Autoencoders (Ordinary type)
the function returns a fully trained auto-encoder based ELM

14 giorni ago | 42 downloads |

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RUL prediction (C-MAPSS dataset)
Dynamic Adaptation for Length Changeable Weighted Extreme Learning Machine

2 mesi ago | 17 downloads |

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Submitted


Extreme Learning Machine for classification and regression
a single hidden layer feed-forward network for regression or classification Trained based on ELM.

6 mesi ago | 54 downloads |

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Backpropagation for training an MLP
this code returns a fully trained MLP for regression using back propagation of the gradient. I dedicate this work to my son :"Lo...

6 mesi ago | 96 downloads |

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Restricted Boltzmann Machine
contrastive divergence for training an RBM is presented in details. I dedicate this work To my son "BERGHOUT Loukmane"

6 mesi ago | 15 downloads |

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Submitted


training of sparse neural network
Training of single hidden layer feedforward network for classification and regression based on L1 norm optimization.

6 mesi ago | 7 downloads |

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PSO for training a regular Autoencoder.
we used particle swarm optimization (PSO) for training an Autoencoder.

6 mesi ago | 10 downloads |

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Sparse Autoencoder
These codes returns a fully traned Sparse Autoencoder

7 mesi ago | 12 downloads |

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Denoising Autoencoder
In this code a full version of denoising autoencoder is presented.

8 mesi ago | 27 downloads |

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Basic learning rules for Rosenblatt perceptron
In these codes we introduce in details the basic learning rules of Rosenblatt perceptron.

8 mesi ago | 2 downloads |

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Convolutional neural networks CNNs (enjoy)
a full version of local receptive field Convolutional neural network is presented in this toolbox.

10 mesi ago | 51 downloads |

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Submitted


discover our first extreme learning machine gui toolbox
the most complicated and well known variants of ELM are presented in this tool box

10 mesi ago | 19 downloads |

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Contractive autoencoders
in these codes a set of functions created to fully train a Contractive Autoencoder.

10 mesi ago | 3 downloads |

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Answered
How to build a not fully-connected neural network step-by-step?
you mean like this one, your question is big , i did it once; but i can give you refrences : read about ELM-LRF

10 mesi ago | 0

Answered
Unknown Future Prediction by Using ANN
I attached this file ,use this function it is great for norlmalization, but befor you normalize your data between 0 and 1 , i me...

10 mesi ago | 0

| accepted

Answered
Can we change the input size of a pretrained network for transfer learning
yes this methode is cold: 1- if you are changing the neumber of neurons from N to n where N>n: this is called :'constructive...

10 mesi ago | 0

Answered
I need to know how to add noise in stacked denoising autoencoders. The coding
you dont have to do that, chek my code her it is verry easy: https://www.mathworks.com/matlabcentral/fileexchange/71115-denoisi...

10 mesi ago | 0

Answered
Hello; nedd help in order to learn programmation
u can use this one here it is very simple (do not forget to leave a comment and rate the application ) Merci. https://www.mathw...

10 mesi ago | 0

| accepted

Answered
Feature Extraction using deep autoencoder
1) you must create a data set of this windows , dataset =[window1;window2; window3 ...................]. 2) train these datase...

10 mesi ago | 0

Answered
non-linear dimension reduction via Autoencoder
1) try to normalize you data first, between 0 and 1. 2) use these autoencoders and tell me the difference https://www.mathwork...

10 mesi ago | 0

Answered
L2 regularization in sparse stacked autoencoders not clear to me
i didnt undrestand your question , could make more clear , there is no k and L2 parameters in the link . could you give us an ...

10 mesi ago | 0

Answered
How to create Autoencoder whit different input and output
autoencoders are used to this purpose the input must be equal the the target ; this is why they named as autoencoders (they enco...

10 mesi ago | 0

Answered
Retraining Deep denoising Autoencoder
you will nerver long use the speach frames in the second DAEs, -first: you will encode your input frames with the first DAs. ...

10 mesi ago | 0

Answered
How are the features obtained in a sparse autoencoder?
in spearse autoencoders , a set of the original images mapped to the output layer passing by the hidden layer, where the output...

10 mesi ago | 0

Submitted


multilayers perceptron based Extreme Learning Machine
Training neural networks with (MLFN) multiple hidden layers with feed-forward type for regression or classification.

11 mesi ago | 23 downloads |

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Answered
code running for infinite while plotting my array for correlation
if you want to plot Rx , then you should plot B not C, and you can't plot B vs C in this example because C and B they dont have ...

11 mesi ago | 1

| accepted

Question


How to generate a similar samples from certain distribution ?
I trained a neural net with some samples (images), and i want to generate a new similar samples to the original ones to see the ...

11 mesi ago | 0 answers | 0

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answers

Answered
what is meant by sigpara and sigpara1 in code
inside the code you will find the answer; just check the authors definitions of inputs and outputs you will find it there

11 mesi ago | 0

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