Zobrazeno 1 - 10 of 81 pro vyhledávání: '"Shushan Qiao"'
1
Akademický článek
A Dual-Wordline 6T SRAM Computing-In-Memory Macro Featuring Full Signed Multi-Bit Computation for Lightweight Networks
Autor: Zupei Gu, Shukao Dou, Heng You, Yi Zhan, Shushan Qiao, Yumei Zhou
Publikováno v: IEEE Access, Vol 12, Pp 35195-35203 (2024)
In this paper, we present an analog-mixed-signal 6T SRAM computing-in-memory (CIM) macro. The macro uses dual-wordline 6T bitcells to reduce power consumption and write-disturb issues. The macro also proposes an analog computation logic circuit for h
Externí odkaz: https://doaj.org/article/1c79512992b243f7adcd477e931aec60
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2
Akademický článek
An Ultra-Small Area and High-Sensitivity Wireless Receiver for ISM and MICS Band Application
Autor: Wenya Chen, Haohan Yang, Shushan Qiao
Publikováno v: IEEE Access, Vol 11, Pp 99046-99057 (2023)
In this work, a 0.43mm2 high-sensitivity low-intermediate-frequency (low-IF) receiver under $0.18~\mu \text{m}$ technology is reported for Industrial Scientific Medical (ISM) and Medical Implant Communications Service (MICS) band applications, which
Externí odkaz: https://doaj.org/article/e3407a3a7a9943fea50d1c6463f314d0
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3
Akademický článek
Blended Glial Cell’s Spiking Neural Network
Autor: Liying Tao, Pan Li, Meihua Meng, Zonglin Yang, Xiaozhuang Liu, Jinhua Hu, Ji Dong, Shushan Qiao, Tianchun Ye, Delong Shang
Publikováno v: IEEE Access, Vol 11, Pp 43566-43582 (2023)
Spiking Neural Networks (SNNs), the third generation of artificial neural networks, have been widely employed. However, the realization of advanced artificial intelligence is challenging due to the dearth of efficient spatiotemporal information integ
Externí odkaz: https://doaj.org/article/89d69bfd70b94b73b8084cf6693d5564
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4
Akademický článek
An Efficient im2row-Based Fast Convolution Algorithm for ARM Cortex-M MCUs
Autor: Peng Wang, Xiaoqin Wang, Rui Luo, Dingyi Wang, Mengjie Luo, Shushan Qiao, Yumei Zhou
Publikováno v: IEEE Access, Vol 9, Pp 124384-124395 (2021)
With the rise of IoT and edge computing, deploying neural networks (NNs) on low-power edge computing devices is drawing more and more attention. In NNs, convolutional layers take up the majority of the computing cycles, especially when NNs are implem
Externí odkaz: https://doaj.org/article/36c0991e3632448ca916649b4998c449
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6
Akademický článek
A 7.4-Bit ENOB 600 MS/s FPGA-Based Online Calibrated Slope ADC without External Components
Autor: Mengdi Zhang, Ye Zhao, Yong Chen, Paolo Crovetti, Yanji Wang, Xinshun Ning, Shushan Qiao
Publikováno v: Sensors, Vol 22, Iss 15, p 5852 (2022)
A slope analog-to-digital converter (ADC) amenable to be fully implemented on a digital field programmable gate array (FPGA) without requiring any external active or passive components is proposed in this paper. The amplitude information, encoded in
Externí odkaz: https://doaj.org/article/5c9c604ec4c74441a87dece98053da77
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