Global exponential stability and periodicity of reaction–diffusion delayed recurrent neural networks with Dirichlet boundary conditions

By Junguo Lu. 2008

312 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/46fcdd0ba3d9e494b300650576b6c3d18f4f453d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Xinsong Yang
2. Zhichun Yang
3. Jinde Cao

In Computer Networks and Communications

1. Xinsong Yang
2. Zhichun Yang
3. Jinde Cao
4. Wenwu Yu
5. Guanrong Chen
6. Jun Wang
7. Jinhu Lu
8. D.W.C. Ho

In Electrical and Electronic Engineering

1. Xinsong Yang
2. Zhichun Yang
3. Jinde Cao

Citations in the corpus

• Synchronization of Coupled Reaction-Diffusion Neural Networks with Time-Varying Delays via Pinning-Impulsive Controller (2013, methodology): “There are some published papers concerning stability or synchronization of neural networks with reaction-diffusion terms and delays (see [16], [17], [42], [43], and [44]).”
• Existence of solution for a fractional‐order Lotka‐Volterra reaction‐diffusion model with Mittag‐Leffler kernel (2019, unknown): “For this, using (10), we have ||1(t,u) − 1(t, ū1)|| = ‖‖‖‖d∗1 ∂2 ∂x2 u1(t) + r∗ 1 u1[1 − a ∗ 11u1 + a ∗ 12u2 − a ∗ 13u3]”