Mokhtar Nibouche
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience
- Artificial Intelligence
- Cellular and Molecular Neuroscience
- Co-authors
- Ahmed BouridaneOmar NiboucheTony PipeMartin J. PearsonChris MelhuishBen MitchinsonKevin GurneyDanny Crookes
- Topics
- Image and Signal Denoising Methods (11 papers)Adaptive Control of Nonlinear Systems (9 papers)Advanced Data Compression Techniques (9 papers)
- Journals
- Signal ProcessingInternational Journal of Robust and Nonlinear ControlIEEE Robotics and Automation Letters
- Partner nations
- United KingdomAlgeriaSaudi Arabia
In The Last Decade
Mokhtar Nibouche
52 papers receiving 367 citations
Peers
Comparison fields: 5 of 58
- Electrical and Electronic Engineering 142
- Computer Vision and Pattern Recognition 102
- Cognitive Neuroscience 91
- Artificial Intelligence 86
- Cellular and Molecular Neuroscience 61
Countries citing papers authored by Mokhtar Nibouche
This map shows the geographic impact of Mokhtar Nibouche's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mokhtar Nibouche with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mokhtar Nibouche more than expected).
Fields of papers citing papers by Mokhtar Nibouche
This network shows the impact of papers produced by Mokhtar Nibouche. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mokhtar Nibouche. The network helps show where Mokhtar Nibouche may publish in the future.
Co-authorship network of co-authors of Mokhtar Nibouche
This figure shows the co-authorship network connecting the top 25 collaborators of Mokhtar Nibouche. A scholar is included among the top collaborators of Mokhtar Nibouche based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mokhtar Nibouche. Mokhtar Nibouche is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 12 | |
| 5 | 8 | |
| 6 | 3 | |
| 7 | Mathematical modelling analysis of male urine flow traces | 0 |
| 8 | A bi-dimensional empirical mode decomposition based watermarking scheme | 4 |
| 9 | 1 | |
| 10 | 6 | |
| 11 | Evolvable Embryonics: Promising Early Results to An Automatic Design of Self-Repair Hardware System. | 1 |
| 12 | 92 | |
| 13 | 5 | |
| 14 | 12 | |
| 15 | 19 | |
| 16 | 3 | |
| 17 | 3 | |
| 18 | 4 | |
| 19 | 3 | |
| 20 | 8 |
About Mokhtar Nibouche
Mokhtar Nibouche is a scholar working on Signal Processing, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 55 papers that have together received 389 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (11 papers), Adaptive Control of Nonlinear Systems (9 papers) and Advanced Data Compression Techniques (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (102 citations), Cognitive Neuroscience (91 citations) and Signal Processing (50 citations). Mokhtar Nibouche has collaborated with scholars based in United Kingdom, Algeria and Saudi Arabia. Frequent co-authors include Ahmed Bouridane, Omar Nibouche, Tony Pipe, Martin J. Pearson, Chris Melhuish, Ben Mitchinson, Kevin Gurney, Danny Crookes, Mohamed Tadjine and Anil Alexander. Their work appears in journals such as Signal Processing, International Journal of Robust and Nonlinear Control and IEEE Robotics and Automation Letters.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.