Existence and stability of anti-periodic solutions for impulsive fuzzy Cohen-Grossberge neural networks on time scales

Abstract

ABSTRACT. By applying the method of coincidence degree and constructing suitable Lyapunov functional, some sufficient conditions are established for the existence and global exponential stability of anti-periodic solutions for a kind of impulsive fuzzy Cohen-Grossberg neural networks on time scales. Moreover an example is given to illustrate our results.

New p-th Moment Exponential Stability Criteria for FCNNs with Time-Varying Delays and Stochastic Effects

“…These models combined fuzzy operation (fuzzy AND and fuzzy OR) with cellular neural networks. Recently scholars have found that FCNNs are useful in image processing, optimization and control [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25]. The sufficient stability criteria have become one of research topic in these models.…”