Name
Title | ||
|---|---|---|
Stability analysis of Riemann-Liouville fractional-order neural networks with reaction-diffusion terms and mixed time-varying delays |
Abstract | ||
|---|---|---|
The stability analysis of time-delay neural networks with reaction-diffusion terms in the sense of Riemann–Liouville derivative is still an open problem, which will be considered in this paper. We first extend a new inequality on Riemann–Liouville fractional-order derivative, which plays an important role in the subsequent proof. Using the Lyapunov direct method, Jensen’s integral inequality, and the linear matrix inequality (LMI) method, several easy-to-test criteria expressed by system parameters and given parameters are given to ensure the stability of the system under consideration. The advantage of our method is that we can directly calculate the integral-order derivative of the Lyapunov function, which can be very convenient to test the stability of practical system. Finally, the validity and conciseness of the results are verified by numerical simulation. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.neucom.2020.12.053 | Neurocomputing |
Keywords | DocType | Volume |
Stability,Riemann–Liouville,Fractional-order neural network,Reaction-diffusion,Mixed time-varying delays | Journal | 431 |
ISSN | Citations | PageRank |
0925-2312 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiang Wu | 1 | 3 | 4.43 |
| Shutang Liu | 2 | 51 | 11.49 |
| Yin Wang | 3 | 12 | 9.28 |