Finite-time anti-synchronization of neural networks with time-varying delays.

In this paper, we are concerned with the anti-synchronization of master–slave neural networks with time delays. By dividing the whole anti-synchronization process into two procedures: the absolute value of error state e i ( t ) flowing from the initial state to 1, then from 1 to 0, i = 1 , … , n , it gets a new viewpoint and a clear illustration on how controller works to the systems. And combining the H o ¨ lder inequality and other techniques, rigorous analysis gives that, each component of error state e ( t ) ( t  ≥ 0) would flow to 1 in finite time, and continue to flow to 0 in fixed time. A numerical example is presented to illustrate the efficiency and effectiveness of our obtained results. [ABSTRACT FROM AUTHOR]