The following publications are possibly variants of this publication:
- Training, Programming, and Correction Techniques of Memristor-Crossbar Neural Networks with Non-Ideal Effects such as Defects, Variation, and Parasitic ResistanceTien Van Nguyen, Jiyong An, Seokjin Oh. asicon 2021: 1-4 [doi]
- Defect-Tolerant and Energy-Efficient Training of Multi-Valued and Binary Memristor Crossbars for Near-Sensor Cognitive ComputingKhoa Van Pham, Tien Van Nguyen, Kyeong-Sik Min. asicon 2019: 1-4 [doi]
- Quantization, training, parasitic resistance correction, and programming techniques of memristor-crossbar neural networks for edge intelligenceTien Van Nguyen, Jiyong An, Seokjin Oh, Son Ngoc Truong, Kyeong-Sik Min. neuromorphic, 2(3):32001, 2022. [doi]
- Comparative Study on Quantization-Aware Training of Memristor Crossbars for Reducing Inference Power of Neural Networks at The EdgeTien Van Nguyen, Jiyong An, Kyeong-Sik Min. ijcnn 2021: 1-6 [doi]
- Interconnect networks for memristor crossbarLei Xie, Hoang Anh Du Nguyen, Mottaqiallah Taouil, Said Hamdioui, Koen Bertels. NANOARCH 2015: 124-129 [doi]
- Neuron Deactivation Scheme for Defect-Tolerant Memristor Neural NetworksSeokjin Oh, Jiyong An, Kyeong-Sik Min. mocast 2022: 1-4 [doi]