TOSAM: An Energy-Efficient Truncation-and Rounding-Based Scalable Approximate Multiplier S Vahdat, M Kamal, A Afzali-Kusha, M Pedram IEEE Transactions on Very Large Scale Integration (VLSI) Systems 27 (5 …, 2019 | 146 | 2019 |
TruncApp: A truncation-based approximate divider for energy efficient DSP applications S Vahdat, M Kamal, A Afzali-Kusha, M Pedram, Z Navabi Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017 …, 2017 | 67 | 2017 |
LETAM: A low energy truncation-based approximate multiplier S Vahdat, M Kamal, A Afzali-Kusha, M Pedram Computers & Electrical Engineering 63, 1-17, 2017 | 57 | 2017 |
Reliability Enhancement of Inverter-Based Memristor Crossbar Neural Networks Using Mathematical Analysis of Circuit Non-Idealities S Vahdat, M Kamal, A Afzali-Kusha, M Pedram IEEE Transactions on Circuits and Systems I: Regular Papers 68 (10), 4310-4323, 2021 | 12 | 2021 |
INTERSTICE: Inverter-based memristive neural networks discretization for function approximation applications S Vahdat, M Kamal, A Afzali-Kusha, M Pedram IEEE Transactions on Very Large Scale Integration (VLSI) Systems 28 (7 …, 2020 | 12 | 2020 |
LATIM: Loading-aware offline training method for inverter-based memristive neural networks S Vahdat, M Kamal, A Afzali-Kusha, M Pedram IEEE Transactions on Circuits and Systems II: Express Briefs 68 (10), 3346-3350, 2021 | 9 | 2021 |
Offline Training Improvement of Inverter-Based Memristive Neural Networks Using Inverter Voltage Characteristic Smoothing S Vahdat, M Kamal, A Afzali-Kusha, M Pedram IEEE Transactions on Circuits and Systems II: Express Briefs 67 (12), 3442-3446, 2020 | 6 | 2020 |
Loading-aware reliability improvement of ultra-low power memristive neural networks S Vahdat, M Kamal, A Afzali-Kusha, M Pedram IEEE Transactions on Circuits and Systems I: Regular Papers 68 (8), 3411-3421, 2021 | 4 | 2021 |
Ultralow-Power Implementation of Neural Networks Using Inverter-Based Memristive Crossbars S Vahdat, M Kamal, A Afzali-Kusha, M Pedram Frontiers of Quality Electronic Design (QED) AI, IoT and Hardware Security …, 2023 | | 2023 |