In this paper, we consider a class of delayed quaternion-valued cellular neural networks (DQVCNNs) with impulsive effects. By using a novel continuation theorem of coincidence degree theory, the existence of anti-periodic solutions for DQVCNNs is obtained with or without assuming that the activation functions are bounded. Furthermore, by constructing a suitable Lyapunov function, some sufficient conditions are derived to guarantee the global exponential stability of anti-periodic solutions for DQVCNNs. Our results are new and complementary to the known results even when DQVCNNs degenerate into real-valued or complex-valued neural networks. Finally, an example is given to illustrate the effectiveness of the obtained results.
KEYWORDSanti-periodic solution, neural networks, quaternion, stabilitywhere q 0 , q 1 , q 2 , q 3 are real numbers and the elements i, j, and k obey the Hamilton's multiplication rules:In the past two decades, the theory of quaternion has been found a lot of applications in many fields such as such as attitude control, quantum mechanics, robotics, computer graphics, and so on. 26-30 Quaternion-valued neural networks (QVNNs), Math Meth Appl Sci. 2019;42:5-23.wileyonlinelibrary.com/journal/mma