Exponential stability of inertial BAM neural networks with time-varying delay via periodically intermittent control

In this paper, we study global exponential stability problem for inertial BAM neural networks with time-varying delay via periodically intermittent control. By utilizing suitable variable substitution, the second-order system can be transformed into first-order differential equations. It is shown that the states of the inertial BAM neural networks with time-varying delay via periodically intermittent control can be globally exponential stabilized with a desired oribis under the designed intermittent controller. Finally, a typical example is chosen to illustrate the validation of the theoretical results.