The global exponential stabilization and lag synchronization control of delayed inertial neural networks (INNs) are investigated. By constructing nonnegative function and employing inequality techniques, several new results about exponential stabilization and exponential lag synchronization are derived via adaptive control. And the theoretical outcomes are developed directly from the INNs themselves without variable substitution. In addition, the synchronization results are also applied to image encryption and decryption. Finally, an example is presented to illustrate the validity of the derived results.

中文翻译：

---

具有时滞的惯性神经网络的全局指数稳定和滞后同步控制。

研究了时滞惯性神经网络的全局指数镇定和滞后同步控制。通过构造非负函数并采用不等式技术，通过自适应控制获得了一些关于指数稳定和指数滞后同步的新结果。理论成果直接来自国际非专利名称本身，没有变量替代。此外，同步结果还应用于图像加密和解密。最后，给出一个例子来说明导出结果的有效性。