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ORCIDSayed Alireza Sadrossadat
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2020 – today
- 2024
[j13]Maedeh Azodi, Sayed Alireza Sadrossadat
, Yvon Savaria:
Nonlinear Circuit Macromodeling Using New Heterogeneous-Layered Deep Clockwork Recurrent Neural Network. IEEE Access 12: 89506-89519 (2024)- [j12]Sayed Alireza Sajjadi, Sayed Alireza Sadrossadat, Ali Moftakharzadeh, Morteza Nabavi, Mohamad Sawan:
Yield Maximization of Flip-Flop Circuits Based on Deep Neural Network and Polyhedral Estimation of Nonlinear Constraints. IEEE Access 12: 113944-113959 (2024) - [j11]Fatemeh Charoosaei, Amin Faraji, Sayed Alireza Sadrossadat, Ali Mirvakili, Weicong Na, Feng Feng, Qi-Jun Zhang:
High-Speed Nonlinear Circuit Macromodeling Using Hybrid-Module Clockwork Recurrent Neural Network. IEEE Trans. Circuits Syst. I Regul. Pap. 71(2): 767-780 (2024) - [j10]Amin Faraji, Sayed Alireza Sadrossadat, Jing Jin, Weicong Na, Feng Feng, Qi-Jun Zhang:
Hybrid Batch-Normalized Deep Feedforward Neural Network Incorporating Polynomial Regression for High-Dimensional Microwave Modeling. IEEE Trans. Circuits Syst. I Regul. Pap. 71(3): 1245-1258 (2024) - [j9]Sayed Alireza Sajjadi, Sayed Alireza Sadrossadat, Ali Moftakharzadeh, Morteza Nabavi, Mohamad Sawan:
DNN-Based Optimization to Significantly Speed Up and Increase the Accuracy of Electronic Circuit Design. IEEE Trans. Circuits Syst. I Regul. Pap. 71(3): 1273-1284 (2024) - [j8]Saeedeh Zebhi, Sayed Alireza Sadrossadat, Weicong Na, Qi-Jun Zhang:
Macromodeling of Nonlinear High-Speed Circuits Using Novel Hybrid Bidirectional High-Order Deep Recurrent Neural Network. IEEE Trans. Circuits Syst. I Regul. Pap. 71(8): 3740-3753 (2024) - 2023
- [j7]Mostafa Noohi, Amin Faraji, Sayed Alireza Sadrossadat, Ali Mirvakili, Ali Moftakharzadeh:
Modeling and implementation of a novel active voltage balancing circuit using deep recurrent neural network with dropout regularization. Int. J. Circuit Theory Appl. 51(5): 2351-2374 (2023) - [j6]Amin Faraji, Sayed Alireza Sadrossadat, Weicong Na, Feng Feng, Qi-Jun Zhang:
A New Macromodeling Method Based on Deep Gated Recurrent Unit Regularized With Gaussian Dropout for Nonlinear Circuits. IEEE Trans. Circuits Syst. I Regul. Pap. 70(7): 2904-2915 (2023) - 2022
- [j5]Amin Faraji, Sayed Alireza Sadrossadat, Mahdi Yazdian Dehkordi, Morteza Nabavi, Yvon Savaria:
A Hybrid Approach Based on Recurrent Neural Network for Macromodeling of Nonlinear Electronic Circuits. IEEE Access 10: 127996-128006 (2022) - [j4]Zohreh Naghibi, Sayed Alireza Sadrossadat, Saeed Safari:
Adjoint recurrent neural network technique for nonlinear electronic component modeling. Int. J. Circuit Theory Appl. 50(4): 1119-1129 (2022) - 2021
- [j3]Mostafa Noohi, Ali Mirvakili, Sayed Alireza Sadrossadat:
Modeling and implementation of nonlinear boost converter using local feedback deep recurrent neural network for voltage balancing in energy harvesting applications. Int. J. Circuit Theory Appl. 49(12): 4231-4247 (2021) - [j2]Mostafa Noohi, Ali Mirvakili, Sayed Alireza Sadrossadat:
Cover Image. Int. J. Circuit Theory Appl. 49(12): i (2021)
2010 – 2019
- 2019
- [j1]Zohreh Naghibi, Sayed Alireza Sadrossadat, Saeed Safari:
Dynamic behavioral modeling of nonlinear circuits using a novel recurrent neural network technique. Int. J. Circuit Theory Appl. 47(7): 1071-1085 (2019)
2000 – 2009
- 2009
- [c1]Sayed Alireza Sadrossadat, Minoo Mirsaeedi, Kumaraswamy Ponnambalam, Mohab H. Anis:
Framework for statistical design of a flip-flop. ICECS 2009: 679-682
Coauthor Index
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