Track Control of Complex-valued Recurrent Neural Networks Based on the Hanaly’s Inequality

This paper discusses the track control problem of complex-valued neural networks (CVNNs) with time delay. By defining the suitable norm, we directly investigate globally asymptotically stable of CVNNs. With the Hanaly's inequality and analysis techniques, we derive a sufficient condition which can make the state of CVNNs globally exponentially track the given reference trace. At last, one illustrative example verifies our result.