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This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
Use the mouse wheel or scroll gestures to zoom into the graph.
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Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Faraji, A., Sadrossadat, S. A., Moftakharzadeh, A., Nabavi, M., & Savaria, Y. (2023). Deep Independent Recurrent Neural Network Technique for Modeling Transient Behavior of Nonlinear Circuits. IEEE Transactions on Components, Packaging and Manufacturing Technology, 13(5), 688-699. External link
Moradi Chaleshtori, R., Saboohi, A., Faraji, A., Alireza Sadrossadat, S., Moftakharzadeh, A., & Savaria, Y. (2025). Long Short-Term Memory Neural Network Combined With a Hybrid-modular Clockwork Structure for Transient Modeling of Nonlinear Circuits. IEEE Access, 13, 107979-107993. External link
Sajjadi, S. A., Sadrossadat, S. A., Moftakharzadeh, A., Nabavi, M., & Sawan, M. (2024). Yield maximization of flip-flop circuits based on deep neural network and polyhedral estimation of nonlinear constraints. IEEE Access, 12, 113944-113959. Available
Sajjadi, S. A., Sadrossadat, S. A., Moftakharzadeh, A., Nabavi, M., & Sawan, M. (2024). DNN-Based Optimization to Significantly Speed Up and Increase the Accuracy of Electronic Circuit Design. IEEE Transactions on Circuits and Systems I: Regular Papers, 12 pages. External link