As an important tool to study practical problems of biology, engineering and image processing, the cellular neural networks (CNNs) has caused more and more attention. Some interesting results about the existence of solution for cellular neural networks have been obtained. In this paper, by means of iterative analysis, the existence of periodic solution and the uniform stability of the equilibrium point of impulsive Hopfield cellular neural networks with distributed delays are considered. Some new results are obtained.

Oscillatory properties of all solutions for nonlinear impulsive hyperbolic equations with delays under the Robin boundary condition are discussed, several criteria are established by the mean method. The results extend the oscillation of impulsive differential equations to impulsive partial differential equations with delays.

In order to solve the fault location problem of single phase to-earth fault in non-effectively grounded distribution network, a new fault location method based on transient frequency of zero-mode current was presented. The difference of transient frequency of zero-mode current between detecting points before and after the fault point is analyzed. This method is realized by the distribution automation (DA) system and does not require additional equipment. The zero-mode current is detected and the frequency of its transient component is calculated by the feeder terminal unit (FTU). The fault section can be located by master station according to comparing the transient frequency at different detecting point on the fault feeder. Results of digital simulation demonstrated the accuracy and feasibility of this method.

As an important tool to study practical problems of biology, engineering and image processing, the cellular neural networks (CNNs) has caused more and more attention. Some interesting results about the existence of solution for cellular neural networks have been obtained. In this paper, by means of iterative analysis, the existence and uniqueness of anti-periodic solution of delayed cellular neural networks with impulsive effects are considered. Some new results are obtained.