Ali R. Abd Ellah - IEEE Xplore Author Profile
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Ali R. Abd Ellah

Publications
2
Citations
18
Publications by Year
20142015
Co-Authors:
Image of author Ali R. Abd Ellah

Ali R. Abd Ellah

Affiliation

Electrical Engineering Dept
Al-Azhar University
Cairo, EG

Publication Topics

Biography

Ali Refaee Abd Ellah Mohamed, received his BSc degree in electronics & communication engineering from Al-Azhar University, Qena, Egypt in 2009, He is currently working toward MSc degree in electrical engineering from Al-Azhar University, Cairo, Egypt. He is currently a teaching assistant in Electrical Engineering Department, electronics & communication branch, faculty of engineering, Al-Azhar University, Qena, Egypt. His current research interests are the robustness of artificial neural networks learning algorithms, and ANN applications. He has 2 publications in international journals. E-mail: ali_refaee2000@yahoo.com, ali_refaee2000@azhar.edu.eg(Based on document published on 2 March 2015).
Publications
2
Citations
18
Publications by Year
20142015
Co-Authors:
Author's Published Works

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Comparison of different backpropagation training algorithms using robust M-estimators performance functions

Ali R. Abd Ellah;Mohamed H. Essai;Ahmed Yahya

2015 Tenth International Conference on Computer Engineering & Systems (ICCES)
Year: 2015 | Conference Paper |
Cited by: Papers (11)
Artificial neural networks are one of the most popular and promising areas of artificial intelligence research. Training data containing outliers are often a problem for supervised neural networks learning algorithms that may not always come up with acceptable performance. Many robust learning algorithms have been proposed so far to improve the performance of neural networks in the presence of out...Show More

Comparison of different backpropagation training algorithms using robust M-estimators performance functions

Ali R. Abd Ellah;Mohamed H. Essai;Ahmed Yahya

Year: 2015 | Conference Paper |

M-Estimators based activation functions for robust neural network learning

Mohamed H. Essai;Ali R. Abd Ellah

2014 10th International Computer Engineering Conference (ICENCO)
Year: 2014 | Conference Paper |
Cited by: Papers (7)
Multi-layer feed-forward neural networks has been proven to be very successful in many applications, as industrial modeling, classification and function approximations. Training data containing outliers are often a problem for these supervised neural networks learning methods that may not always come up with acceptable performance. Robust neural network learning algorithms are often applied to dea...Show More

M-Estimators based activation functions for robust neural network learning

Mohamed H. Essai;Ali R. Abd Ellah

Year: 2014 | Conference Paper |

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