An Ultralow-Power Real-Time Machine Learning Based fNIRS Motion Artifacts Detection [0.03%]
一种基于实时机器学习的超低功耗fNIRS运动伪迹检测方法
Renas Ercan,Yunjia Xia,Yunyi Zhao et al.
Renas Ercan et al.
Due to iterative matrix multiplications or gradient computations, machine learning modules often require a large amount of processing power and memory. As a result, they are often not feasible for use in wearable devices, which have limited...
Design and implementation of an ultra-low energy FFT ASIC for processing ECG in Cardiac Pacemakers [0.03%]
面向心脏起搏器心电处理的超低能耗FFT专用集成电路的设计与实现
Safwat Mostafa,Eugene B John,Manoj M Panday
Safwat Mostafa
In embedded biomedical applications, spectrum analysis algorithms such as Fast Fourier Transform (FFT) are crucial for pattern detection and has been the focus of continued research. In deeply embedded systems such as cardiac pacemakers, FF...
YongHong Tao,Andreas Hierlemann
YongHong Tao
This paper presents a 15-channel, 30-V, implantable current stimulator for restoring locomotion control after spinal cord injuries. The stimulator features performance specifications comparable to those of large desktop instrumentation: hig...
Demonstrating HW–SW Transient Error Mitigation on the Single-Chip Cloud Computer Data Plane [0.03%]
在单芯片云计算机数据平面上演示软硬件瞬态误差缓解
Rodopoulos, Dimitrios; Papanikolaou, Antonis; Catthoor et al.
Rodopoulos et al.
Orchestrator: Guarding Against Voltage Emergencies in Multithreaded Applications [0.03%]
Orchestrator：防范多线程应用程序中的电压紧急情况
Hu, Xing; Yan, Guihai; Hu et al.
Hu et al.
Lao, Yingjie; Parhi, Keshab K.
Lao
Ye, Jing; Huang, Yu; Hu et al.
Ye et al.
Youssef, Ahmed; Zahran, Mohamed; Anis et al.
Youssef et al.
Rahman, Mohammed Ziaur; Kleeman, Lindsay; Habib et al.
Rahman et al.
Tabkhi, Hamed; Schirner, Gunar
Tabkhi