Dynamic neural network models for time-varying problem solving: a survey on model structures
C Hua, X Cao, Q Xu, B Liao, S Li - IEEE Access, 2023 - ieeexplore.ieee.org
In recent years, neural networks have become a common practice in academia for handling
complex problems. Numerous studies have indicated that complex problems can generally …
complex problems. Numerous studies have indicated that complex problems can generally …
Advances on intelligent algorithms for scientific computing: an overview
C Hua, X Cao, B Liao, S Li - Frontiers in Neurorobotics, 2023 - frontiersin.org
The field of computer science has undergone rapid expansion due to the increasing interest
in improving system performance. This has resulted in the emergence of advanced …
in improving system performance. This has resulted in the emergence of advanced …
A parameter-changing zeroing neural network for solving linear equations with superior fixed-time convergence
L Xiao, Y He, B Liao - Expert Systems with Applications, 2022 - Elsevier
Linear equations (LEs) play an essential role in mathematics. Nevertheless, the vast majority
of fixed-parameter zeroing neural network (ZNN) models are not fast enough to solve LEs …
of fixed-parameter zeroing neural network (ZNN) models are not fast enough to solve LEs …
A robust noise tolerant zeroing neural network for solving time-varying linear matrix equations
A robust noise-tolerant zeroing neural network (ZNN) is introduced for solving time-varying
linear matrix equations (TVLME). The convergence speed of designed neural dynamics is …
linear matrix equations (TVLME). The convergence speed of designed neural dynamics is …
A family of varying-parameter finite-time zeroing neural networks for solving time-varying Sylvester equation and its application
A family of varying-parameter finite-time zeroing neural networks (VPFTZNN) is introduced
for solving the time-varying Sylvester equation (TVSE). The convergence speed of the …
for solving the time-varying Sylvester equation (TVSE). The convergence speed of the …
A parallel computing method based on zeroing neural networks for time-varying complex-valued matrix Moore-Penrose inversion
This paper analyzes the existing zeroing neural network (ZNN) models from the perspective
of control theory. It proposes an exclusive ZNN model for solving the dynamic complex …
of control theory. It proposes an exclusive ZNN model for solving the dynamic complex …
A variable-parameter ZNN with predefined-time convergence for dynamic complex-valued Lyapunov equation and its application to AOA positioning
Y He, L Xiao, F Sun, Y Wang - Applied Soft Computing, 2022 - Elsevier
Zeroing neural network (ZNN) is an effective means of handling the dynamic Lyapunov
equation. However, the conventional ZNN's convergence speed relies heavily on its initial …
equation. However, the conventional ZNN's convergence speed relies heavily on its initial …
A nonlinear zeroing neural network and its applications on time-varying linear matrix equations solving, electronic circuit currents computing and robotic manipulator …
J Jin, W Chen, L Zhao, L Chen, Z Tang - Computational and Applied …, 2022 - Springer
Zeroing neural network has proved its powerful abilities and efficiency in solving various
time-varying problems, and its convergence and robustness have been deeply studied in …
time-varying problems, and its convergence and robustness have been deeply studied in …
A deep ensemble dynamic learning network for corona virus disease 2019 Diagnosis
Z Zhang, B Chen, Y Luo - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Corona virus disease 2019 is an extremely fatal pandemic around the world. Intelligently
recognizing X-ray chest radiography images for automatically identifying corona virus …
recognizing X-ray chest radiography images for automatically identifying corona virus …
A jump-gain integral recurrent neural network for solving noise-disturbed time-variant nonlinear inequality problems
Z Zhang, Y Song, L Zheng, Y Luo - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Nonlinear inequalities are widely used in science and engineering areas, attracting the
attention of many researchers. In this article, a novel jump-gain integral recurrent (JGIR) …
attention of many researchers. In this article, a novel jump-gain integral recurrent (JGIR) …