Fu-Chun Chang
According to our database1,
Fu-Chun Chang
authored at least 13 papers
between 1992 and 2024.
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Bibliography
2024
An 8b-Precision 6T SRAM Computing-in-Memory Macro Using Time-Domain Incremental Accumulation for AI Edge Chips.
IEEE J. Solid State Circuits, July, 2024
2023
8-b Precision 8-Mb ReRAM Compute-in-Memory Macro Using Direct-Current-Free Time-Domain Readout Scheme for AI Edge Devices.
IEEE J. Solid State Circuits, 2023
A 28nm Nonvolatile AI Edge Processor using 4Mb Analog-Based Near-Memory-Compute ReRAM with 27.2 TOPS/W for Tiny AI Edge Devices.
Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023
2022
Two-Way Transpose Multibit 6T SRAM Computing-in-Memory Macro for Inference-Training AI Edge Chips.
IEEE J. Solid State Circuits, 2022
Efficient token circulation strategies against misers in device-to-device relay using token-based incentive mechanisms.
IET Commun., 2022
A 28nm 1Mb Time-Domain Computing-in-Memory 6T-SRAM Macro with a 6.6ns Latency, 1241GOPS and 37.01TOPS/W for 8b-MAC Operations for Edge-AI Devices.
Proceedings of the IEEE International Solid-State Circuits Conference, 2022
A 40-nm, 2M-Cell, 8b-Precision, Hybrid SLC-MLC PCM Computing-in-Memory Macro with 20.5 - 65.0TOPS/W for Tiny-Al Edge Devices.
Proceedings of the IEEE International Solid-State Circuits Conference, 2022
An 8-Mb DC-Current-Free Binary-to-8b Precision ReRAM Nonvolatile Computing-in-Memory Macro using Time-Space-Readout with 1286.4-21.6TOPS/W for Edge-AI Devices.
Proceedings of the IEEE International Solid-State Circuits Conference, 2022
A 22nm 4Mb STT-MRAM Data-Encrypted Near-Memory Computation Macro with a 192GB/s Read-and-Decryption Bandwidth and 25.1-55.1TOPS/W 8b MAC for AI Operations.
Proceedings of the IEEE International Solid-State Circuits Conference, 2022
2021
IEEE Trans. Circuits Syst. I Regul. Pap., 2021
A 22nm 4Mb 8b-Precision ReRAM Computing-in-Memory Macro with 11.91 to 195.7TOPS/W for Tiny AI Edge Devices.
Proceedings of the IEEE International Solid-State Circuits Conference, 2021
2019
A 0.5V Real-Time Computational CMOS Image Sensor with Programmable Kernel for Always-On Feature Extraction.
Proceedings of the IEEE Asian Solid-State Circuits Conference, 2019
1992
A new art-based neural architecture for pattern classification and image enhancement without prior knowledge.
Pattern Recognit., 1992