Li Qiu
3 Papers
Li Qiu is an academic researcher. The author has contributed to research in topics: Computer science & Robustness (evolution). The author has an hindex of 2, co-authored 3 publications.
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Papers
A noise tolerant parameter-variable zeroing neural network and its applications
TL;DR: In this article , a noise-tolerant parameter-variable zeroing neural network (NTPVZNN) model for solving dynamic Sylvester matrix equations (DSME) is realized, and its fixedtime convergence and robustness to noises are verified by rigorous mathematical analysis and numerical simulation results.
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Improved Recurrent Neural Networks for Text Classification and Dynamic Sylvester Equation Solving
TL;DR: An improved fixed-time convergent recurrent neural network (IFTCRNN) model for time-varying problems solving is constructed and achieves fixed-time convergence and strong robustness to noises in time-varying Sylvester matrix equation solving, dynamic matrix inversion and robot manipulator trajectory tracking.
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A robust fast convergence zeroing neural network and its applications to dynamic Sylvester equation solving and robot trajectory tracking
TL;DR: In this paper , a robust fast convergence zeroing neural network (RFCZNN) is proposed to find the theoretical solution of a dynamic Sylvester equation (DSE) in noisy environment.