报告题目：Synchronization criteria for delayed discontinuous neural networks via functional differential inclusions
汪东树:华侨大学副教授,主持和参与多项国家和福建省自然科学基金项目，在《IEEE Transactions on Neural Networks and Learning Systems》、《Chaos》、《Proceeding of the American Mathematical Society》等杂志发表多篇学术论文。
摘要：In this talk, we investigate the issue of global exponential synchronization for a class of general neural networks that contains discontinuous activation functions and mixed time delays. Functional differential inclusions and non-smooth analysis theories are used as bases to design continuous and discontinuous controllers such that the discontinuous neural networks can be exponential complete synchronized. This novel approach and its applicability to neural networks with continuous activations are also easily verified. Several numerical examples demonstrate the practicality and effectiveness of the design method.