This dissertation present some qualitative studies on several neural networks models withdelay which includes globally asymptotic stability, globally exponential stability, chaos synchro-nization, multiperiodicity attractivity.
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Some new criteria on globally exponential stability of the networks are obtained.
并且由此定理获得该类网络全局指数稳定的几个判据。
This paper studies the problem of globally exponential stability for the cellular neural networks.
主要考察了一类动态系统——带有不同时间尺度竞争神经网络的全局指数稳定性问题。
Based on the Lagrange formula with constants variables, some new sufficient conditions for ensuring globally exponential stability of such systems are derived.
基于拉格朗日常数变易法，给出这类系统全局指数稳定的一个充分条件。
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