6 papers · 1 filter
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…
SNNF: An SNN-based Near-Sensor Noise Filter for Dynamic Vision Sensors
Yahan Yang, Pradeep Kumar Gopalakrishnan, Chang Chip Hong +1
Dynamic Vision Sensors (DVS) exhibit exceptional dynamic range and low power consumption, making them ideal for edge applications in the Internet of Video Things (IoVT). However, t…
SRAM-Based Compute-in-Memory Accelerator for Linear-decay Spiking Neural Networks
Hongyang Shang, Shuai Dong, Yahan Yang +3
Spiking Neural Networks (SNNs) have emerged as a biologically inspired alternative to conventional deep networks, offering event-driven and energy-efficient computation. However, t…
In-Memory ADC-Based Nonlinear Activation Quantization for Efficient In-Memory Computing
Shuai Dong, Junyi Yang, Biyan Zhou +3
In deep networks, operations such as ReLU and hardware-driven clamping often cause activations to accumulate near the edges of the distribution, leading to biased clustering and su…
An Event-Driven E-Skin System with Dynamic Binary Scanning and real time SNN Classification
Gaishan Li, Zhengnan Fu, Anubhab Tripathi +2
This paper presents a novel hardware system for high-speed, event-sparse sampling-based electronic skin (e-skin)that integrates sensing and neuromorphic computing. The system is bu…
STEMNIST: Spiking Tactile Extended MNIST Neuromorphic Dataset
Anubhab Tripathi, Li Gaishan, Zhengnan Fu +3
Tactile sensing is essential for robotic manipulation, prosthetics and assistive technologies, yet neuromorphic tactile datasets remain limited compared to their visual counterpart…