Abstract
When the states of a system are decided not only by states of the current time and the past time but also by the derivative of the past states, the system can be called a neutral system. The problems of stability and synchronization of neutral neural networks play an important role in the same issues of neural networks. In this chapter, robust stability of neutral neural networks is first discussed.
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