Strong consistence of recursive identification for Wiener systems. - Xiao-Li Hu; Han-Fu Chen (Autom., 2005)

Identification for Wiener Systems with RTF Subsystems. - Xiao-Li Hu; Han-Fu Chen (Eur. J. Control, 2006)

A robust particle filter for state estimation - with convergence results. - Xiao-Li Hu; Thomas B. Schön; Lennart Ljung (CDC, 2007)

A Basic Convergence Result for Particle Filtering. - Xiao-Li Hu; Thomas B. Schön; Lennart Ljung (IEEE Trans. Signal Process., 2008)

An extension of Rosenthal's inequality. - Xiao-Li Hu (Appl. Math. Comput., 2011)

A General Convergence Result for Particle Filtering. - Xiao-Li Hu; Thomas B. Schön; Lennart Ljung (IEEE Trans. Signal Process., 2011)

Bias analysis of continuous-time model identification from filtered sample output data. - Xiao-Li Hu; James S. Welsh (CDC, 2012)

An extension of Young's inequality and its application. - Xiao-Li Hu (Appl. Math. Comput., 2013)

Necessary and sufficient convergence conditions of the instrumental variable method for identification. - Xiao-Li Hu; James S. Welsh (Autom., 2013)

Fundamental Limitations in Energy Detection for Spectrum Sensing. - Xiao-Li Hu; Pin-Han Ho; Limei Peng (J. Sens. Actuator Networks, 2018)

Performance Analysis of Maximum Likelihood Estimation for Transmit Power Based on Signal Strength Model. - Xiao-Li Hu; Pin-Han Ho; Limei Peng (J. Sens. Actuator Networks, 2018)

On uniqueness of sparse signal recovery. - Xiao-Li Hu; Jiajun Wen 001; Wai Keung Wong; Le Tong; Jinrong Cui (Signal Process., 2018)

Statistical Properties of Energy Detection for Spectrum Sensing by Using Estimated Noise Variance. - Xiao-Li Hu; Pin-Han Ho; Limei Peng (J. Sens. Actuator Networks, 2019)

Binary sparse signal recovery algorithms based on logic observation. - Xiao-Li Hu; Jiajun Wen 001; Zhihui Lai 001; Wai Keung Wong; Linlin Shen (Pattern Recognit., 2019)

Continuous-Time Model Identification From Filtered Sampled Data: Error Analysis. - Xiao-Li Hu; James S. Welsh (IEEE Trans. Autom. Control., 2020)

Restricted subgradient descend method for sparse signal learning. - Jiajun Wen 001; Wai Keung Wong; Xiao-Li Hu; Hong-Lin Chu; Zhihui Lai 001 (Int. J. Mach. Learn. Cybern., 2022)