collaborators

8 papers

cs.AR2026

NeuDW-CIM: a 65-nm 0.8-pJ/Sop Reconfigurable Neuromorphic Compute-in-Memory Macro with Nonlinear Dendrites and K-Winners

Junyi Yang, Yahan Yang, Shuai Dong +7

This work presents NeuDW-CIM, a highly efficient neuromorphic Compute-in-Memory (CIM) macro for Spiking Neural Networks (SNNs) implemented in 65 nm CMOS. The design introduces a cu…

eess.SP2026

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…

cs.AR2025

3D Stack In-Sensor-Computing (3DS-ISC): Accelerating Time-Surface Construction for Neuromorphic Event Cameras

Hongyang Shang, Shuai Dong, Ye Ke +1

This work proposes a 3D Stack In-Sensor-Computing (3DS-ISC) architecture for efficient event-based vision processing. A real-time normalization method using an exponential decay fu…

eess.SP2025

1024-Channel 0.8V 23.9-nW/Channel Event-based Compute In-memory Neural Spike Detector

Ye Ke, Zhengnan Fu, Junyi Yang +2

The increasing data rate has become a major issue confronting next-generation intracortical brain-machine interfaces (iBMIs). The scaling number of recording sites requires complex…

cs.AR2025

A 33.6-136.2 TOPS/W Nonlinear Analog Computing-In-Memory Macro for Multi-bit LSTM Accelerator in 65 nm CMOS

Junyi Yang, Xinyu Luo, Ye Ke +7

The energy efficiency of analog computing-in-memory (ACIM) accelerator for recurrent neural networks, particularly long short-term memory (LSTM) network, is limited by the high pro…

cs.AR2025

Near-Memory Architecture for Threshold-Ordinal Surface-Based Corner Detection of Event Cameras

Hongyang Shang, An Guo, Shuai Dong +3

Event-based Cameras (EBCs) are widely utilized in surveillance and autonomous driving applications due to their high speed and low power consumption. Corners are essential low-leve…