基于离散Hopfield神经网络的文献检索智能识别

根据Hopfidd网络中神经元之间的相互连接具有丰富的动力学特性的特点，探究了Hopfield网络模型在文献检索中的运用，指出该网络存在的问题，并提出解决方案．     

基于离散Hopfield神经网络的文献检索智能识别

根据Hopfield网络中神经元之间的相互连接具有丰富的动力学特性的特点,探究了Hopfield网络模型在文献检索中的运用,指出该网络存在的问题,并提出解决方案.     

Synchronization of fractional-order linear complex networks

In this paper, we concentrate on the synchronization problem of fractional-order complex networks with general linear dynamics under connected topology. By introducing a pseudo-state transformation, the problem is converted into an equivalent simultaneous stabilization problem of independent subsystems, which is characterized by nonzero eigenvalues of the Laplacian matrix. Then, sufficient conditions in terms of linear matrix inequalities (LMIs) for synchronization are established, which can be easily solved by efficient convex optimization algorithms. Finally, three examples are provided to illustrate the effectiveness of the proposed method.