Xuan Zeng

TL;DR: The feasibility and effectiveness of applying the blind signal processing and deep learning techniques to biometric human identification is demonstrated, to enable a low algorithm engineering effort and also a high generalization ability.

TL;DR: A weighted expected improvement-based Bayesian optimization approach for automated analog circuit sizing using Gaussian processes as the online surrogate models for circuit performances and extended to handle multi-objective optimization problems.

TL;DR: The proposed wearable cuff-less electrocardiography and photoplethysmogram-based SBP and HR monitoring system is highly wearable, and its robustness is thoroughly evaluated on different modeling strategies and also the unseen data, which are expected to contribute to long-term pervasive hypertension, heart health and fitness management.

TL;DR: This work presents a statistical analysis framework that characterizes the lifetime reliability of nanometer-scale integrated circuits by jointly considering the impact of fabrication-induced process variation and run-time aging effects, and focuses on characterizing circuit threshold voltage lifetime variation.

TL;DR: The HSPICE simulation results show that the write speed and power consumption of the proposed RSP-14T are improved by ~65% and ~50%, respectively, compared with those of the radiation hardened design (RHD)-12T memory cell.