Name
Title | ||
|---|---|---|
Improved Zhang neural network with finite-time convergence for time-varying linear system of equations solving. |
Abstract | ||
|---|---|---|
This paper proposes an improved Zhang neural network (IZNN) for time-varying linear system of equations solving. Such a neural network is activated by an array of continuous sign-bi-power function. Theoretical analysis is provided to show the desired finite-time convergence property of the proposed IZNN. As compared to Zhang neural network activated by an array of discontinuous signum-function, the solution synthesized by the proposed neural network can converge to theoretical solution, while the solution synthesized by the latter oscillates to some extent around the equilibrium point. Moreover, the remarkable finite-time convergence of the proposed IZNN model is corroborated by a simulative example. Simulation results also demonstrate that the proposed neural network is more suitable in engineering applications than Zhang neural network activated by the array of discontinuous signum-function. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.ipl.2019.03.012 | Information Processing Letters |
Keywords | Field | DocType |
Algorithms,Time-varying linear system of equations,Improved Zhang neural network,Sign-bi-power function,Finite-time convergence property | Convergence (routing),Applied mathematics,Discrete mathematics,Zhang neural network,System of linear equations,Equilibrium point,Artificial neural network,Mathematics,Finite time | Journal |
Volume | ISSN | Citations |
147 | 0020-0190 | 2 |
PageRank | References | Authors |
0.37 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuanjiao Lv | 1 | 45 | 3.70 |
| Lin Xiao | 2 | 94 | 15.07 |
| Zhiguo Tan | 3 | 7 | 1.78 |