Finite-Time Convergence and Robustness Analysis of Two Nonlinear Activated ZNN Models for Time-Varying Linear Matrix Equations. - Lin Xiao 002; Lei Jia; Yongsheng Zhang; Zeshan Hu; Jianhua Dai (IEEE Access, 2019)

Design and analysis of new complex zeroing neural network for a set of dynamic complex linear equations. - Lin Xiao 002; Qian Yi; Jianhua Dai; Kenli Li 001; Zeshan Hu (Neurocomputing, 2019)

Performance Benefits of Robust Nonlinear Zeroing Neural Network for Finding Accurate Solution of Lyapunov Equation in Presence of Various Noises. - Lin Xiao 002; Yongsheng Zhang; Zeshan Hu; Jianhua Dai (IEEE Trans. Ind. Informatics, 2019)

Zeroing neural network with comprehensive performance and its applications to time-varying Lyapunov equation and perturbed robotic tracking. - Zeshan Hu; Kenli Li 001; Keqin Li 001; Jichun Li 002; Lin Xiao 002 (Neurocomputing, 2020)

Performance analysis of nonlinear activated zeroing neural networks for time-varying matrix pseudoinversion with application. - Zeshan Hu; Lin Xiao 002; Kenli Li 001; Keqin Li 001; Jichun Li 002 (Appl. Soft Comput., 2021)

A Unified Predefined-Time Convergent and Robust ZNN Model for Constrained Quadratic Programming. - Zeshan Hu; Lin Xiao 002; Jianhua Dai; Yang Xu 013; Qiuyue Zuo; Chubo Liu (IEEE Trans. Ind. Informatics, 2021)

Adams-Bashforth-Type Discrete-Time Zeroing Neural Networks Solving Time-Varying Complex Sylvester Equation With Enhanced Robustness. - Zeshan Hu; Kenli Li 001; Lin Xiao 002; Yaonan Wang 001; Mingxing Duan; Keqin Li 001 (IEEE Trans. Syst. Man Cybern. Syst., 2022)

Protein Sequence Prediction Based on Feature Combination and Attention Mechanism. - Zeshan Hu; Quanli Pei (WI/IAT, 2024)