Impulsive Control of Complex-Valued Neural Networks with Mixed Time Delays and Uncertainties

This paper investigates the global exponential stability of uncertain delayed complex-valued neural networks (CVNNs) under an impulsive controller. Both discrete and distributed time-varying delays are considered, which makes our model more general than previous works. Unlike most existing research methods of decomposing CVNNs into real and imaginary parts, some stability criteria in terms of complex-valued linear matrix inequalities (LMIs) are obtained by employing the complex Lyapunov function method, which is valid regardless of whether the activation functions can be decomposed. Moreover, a new impulsive differential inequality is applied to resolve the difficulties caused by the mixed time delays and delayed impulse effects. Finally, an illustrative example is provided to back up our theoretical results.

Automated summary

This paper investigates the global exponential stability of uncertain delayed complex-valued neural networks under an impulsive controller, proposing stability criteria in terms of complex-valued linear matrix inequalities and a new impulsive differential inequality to address the difficulties caused by mixed time delays and delayed impulse effects. An illustrative example is provided to support the theoretical results.