From the 1 of 9 linked papers with an AI index.
9 papers
TIDE: Trustworthy and Interpretable Battery Degradation Estimation with Contextual Learning and Symbolic Distillation
Wen Yang Tan, Jiawei Li, Fang Liu +4
The paper introduces TIDE, a machine‑learning system that combines battery domain knowledge with operational data to estimate battery health accurately while providing trustworthy…
Symbiotic Backscatter Communication: A Design Perspective on the Modulation Scheme of Backscatter Devices
Yinghui Ye, Shuang Lu, Liqin Shi +2
Symbiotic Backscatter Communication (SBC) has emerged as a spectrum-efficient and low-power communication technology, where backscatter devices (BDs) modulate and reflect incident…
Symbol Detection in Ambient Backscatter Communications Under Residual Time Synchronization Errors
Yinghui Ye, Ying Li, Xiaoli Chu +2
Ambient backscatter communications (AmBC), where a backscatter transmitter (BT) modulates and reflects ambient signals to a backscatter receiver (BR), have been deemed a low-power…
Error Floor of ML-Decoded Spinal Codes in the Finite Blocklength Regime
Aimin Li, Shaohua Wu, Xiaomeng Chen +1
Spinal codes is a new family of capacity-achieving rateless codes that has been shown to achieve better rate performance compared to Raptor codes, Strider codes, and rateless Low-D…
Knowledge-Aware Modeling with Frequency Adaptive Learning for Battery Health Prognostics
Vijay Babu Pamshetti, Wei Zhang, Sumei Sun +3
Battery health prognostics are critical for ensuring safety, efficiency, and sustainability in modern energy systems. However, it has been challenging to achieve accurate and robus…
Vehicle-to-Everything Cooperative Perception for Autonomous Driving
Tao Huang, Jianan Liu, Xi Zhou +5
Achieving fully autonomous driving with enhanced safety and efficiency relies on vehicle-to-everything cooperative perception, which enables vehicles to share perception data, ther…