Publications

J. Xu, Y. Shen, J. Deng, E. Chen, and V. Chen, “A Reinforcement-Learning-Assisted Power Amplifier for RF Fingerprint Generation in 65 nm CMOS,” in IEEE Transactions on Circuits and Systems I: Regular Papers, 2024.

J. Xu, Y. Shen, J. Yi, E. Chen, and V. Chen, “Deep Reinforcement Learning on FPGA for Self-Healing Cryogenic Power Amplifier Control,” IEEE Open Journal of Circuits and Systems, 2023. (paper)

J. Kan, Y. Shen, J. Xu, E. Chen, J. Zhu, and V. Chen, “RF Analog Hardware Trojan Detection through Electromagnetic Side-Channel,” IEEE Open Journal of Circuits and Systems, vol. 3, pp. 237-251, Sep. 2022. (paper)

V. Chen, J. Xu, Y. Shen, and E. Chen, “RF Fingerprint Classification With Combinatorial-Randomness-Based Power Amplifiers and Convolutional Neural Networks,” IEEE Solid-State Circuits Magazine, vol. 14, no. 4, pp. 28-36, Nov. 2022. (paper)

J. Yi, J. Xu, E. Chen, M. Chamanzar, and V. Chen, “Multichannel Many-Class Real-Time Neural Spike Sorting With Convolutional Neural Networks,” IEEE Open Journal of Circuits and Systems, vol. 3, pp. 168-179, Sep. 2022. (paper)

J. Xu, Y. Shen, J. Yi, E. Chen, and V. Chen, “Combinatorial-Randomness-Based Power Amplifier Datasets with RF Fingerprint Classification,” in tinyML Research Symposium, Burlingame, CA, March 2022. (poster) [(presentation)](https://ieeexplore.ieee.org/document/9682436](https://www.youtube.com/watch?v=kPTiwchX5_g)

Y. Shen, J. Xu, J. Yi, E. Chen and V. Chen, “Class-E Power Amplifiers Incorporating Fingerprint Augmentation With Combinatorial Security Primitives for Machine-Learning-Based Authentication in 65 nm CMOS,” in IEEE Transactions on Circuits and Systems I: Regular Papers, doi: 10.1109/TCSI.2022.3141336. (paper)

J. Xu, Y. Shen, E. Chen and V. Chen, “Bayesian Neural Networks for Identification and Classification of Radio Frequency Transmitters Using Power Amplifiers’ Nonlinearity Signatures,” in IEEE Open Journal of Circuits and Systems, vol. 2, pp. 457-471, 2021. (paper)

J. Xu, E. Chen and V. Chen, “Energy-Efficient Data Symbol Detection via Boosted Learning for Multi-Actuator Data Storage Systems,” 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 2021, pp. 1-5. (paper) (demo)

E. Chen, J. Xu, J. -G. Zhu and V. Chen, “Wireless Bayesian Neural Networks with Self-Assembly DNA Memory and Spin-Torque Oscillators,” 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS), 2020, pp. 269-272. (paper)