4 papers
A 32-Channel 3.53-μW Per Channel Brain-Machine Interface SoC Featuring Dual-Threshold Delta-modulation, In-Memory Spike Detection and Bi-SNN Based Motor Decoding
Ye Ke, Zhengnan Fu, Pao-Sheng Vincent Sun +8
With the scaling of sensor channel counts, systems confront challenges in frontend data sensing and on-implant data processing. This work presents a 32-channel fully event-based iB…
SPACE: SPike-Aware Consistency Enhancement for Test-Time Adaptation in Spiking Neural Networks
Xinyu Luo, Kecheng Chen, Pao-Sheng Vincent Sun +3
Spiking Neural Networks (SNNs), as a biologically plausible alternative to Artificial Neural Networks (ANNs), have demonstrated advantages in terms of energy efficiency, temporal p…
Combining SNNs with Filtering for Efficient Neural Decoding in Implantable Brain-Machine Interfaces
Biyan Zhou, Pao-Sheng Vincent Sun, Arindam Basu
While it is important to make implantable brain-machine interfaces (iBMI) wireless to increase patient comfort and safety, the trend of increased channel count in recent neural pro…
Efficient Nonlinear Function Approximation in Analog Resistive Crossbars for Recurrent Neural Networks
Junyi Yang, Ruibin Mao, Mingrui Jiang +9
Analog In-memory Computing (IMC) has demonstrated energy-efficient and low latency implementation of convolution and fully-connected layers in deep neural networks (DNN) by using p…