Control chaos in nonautonomous cellular neural networks using impulsive control methods
Zhenya He, Yifeng Zhang, Lüxi Yang, Yuhui Shi · 2003
Chaotic behavior can be found in nonautonomous cellular neural networks (CNNs). The impulsive control method to control this kind of chaos is used and some satisfactory result are achieved. The condition which ensure existence of periodic solution in the impulse controlled system is provided and proved, and numerical simulation shows the chaos can be eliminated by adding a very small external force. Through observing the time waveform diagram of some controlled periodic orbits, we find the time waveform is very similar to encephalic electric activity or cardiac electric activity in biomedical field study. This illustrate that the nonautonomous CNNs model can successfully model physiological electric response activity signals. Moreover, the physiological explanation is given for the nonautonomous CNNs model.