4 citations · 4 across the 6 of their papers we have counts for
7 papers
Comparative Analysis on Inertia Estimation Algorithms (IEAs) in Providing Proper Frequency Response
Karl M. H. Lai, Yunhe Hou, Kwunhang Wong
The inertia constant H[s] is a fundamental indicator of power system resilience, linking power imbalance between generation and load to frequency deviation. It is essential in freq…
Potentials and Limitations on Different Busbar Protections in Industrial Applications
Karl M. H. Lai, Yunhe Hou, Kwunhang Wong
Busbar protection is a cornerstone of industrial power system reliability, as failures at switchgear can propagate rapidly and extend restoration times. The Taiwan "303 blackout" i…
RRAM-DP: Device-Calibrated Differential Privacy for In-Memory Edge Learning
Kwunhang Wong, Jichang Yang, Karl M. H. Lai +7
Edge Artificial Intelligence of Things (AIoT) systems often collect sensitive data in situ, raising serious privacy concerns. Resistive-switching random-access memory (RRAM) is an…
Towards Secure and Efficient DNN Accelerators via Hardware-Software Co-Design
Wei Xuan, Zihao Xuan, Rongliang Fu +8
The rapid deployment of deep neural network (DNN) accelerators in safety-critical domains such as autonomous vehicles, healthcare systems, and financial infrastructure necessitates…
Parameter Efficient Machine Unlearning on Hybrid Resistive Memory based Compute-in-Memory Accelerators
Ning Lin, Jichang Yang, Yangu He +17
Resistive memory compute-in-memory accelerators provide energy efficient analogue matrix vector multiplication for neural network inference, but frequent reprogramming of analogue…
SNNGX: Securing Spiking Neural Networks with Genetic XOR Encryption on RRAM-based Neuromorphic Accelerator
Kwunhang Wong, Songqi Wang, Wei Huang +8
Biologically plausible Spiking Neural Networks (SNNs), characterized by spike sparsity, are growing tremendous attention over intellectual edge devices and critical bio-medical app…
Older and Wiser: The Marriage of Device Aging and Intellectual Property Protection of Deep Neural Networks
Ning Lin, Shaocong Wang, Yue Zhang +6
Deep neural networks (DNNs), such as the widely-used GPT-3 with billions of parameters, are often kept secret due to high training costs and privacy concerns surrounding the data u…