Complex Networks of Application of Information Processing

在这项研究中，我们研究了复杂网络的性能时，负担得起的神经网络应用于信息处理。我们关注的是具有尺度规则选择的负担得起的神经网络及其学习和泛化能力。我们还提出了一种新的具有社会网络性质的网络结构，并研究了联想记忆的性能。最后，通过实际电路模型实现了所提出的人工神经网络。

In this study, we have investigated the performance of complex networks when the affordable neural network is applied for the information processing. We have focused on the affordable neural networks with scale-rule selection and its learning and generalization abilities. We have also proposed the new network structure which has social network property and have investigated the performance of associative memory. Finally, the proposed artificial neural network was realized by the actual circuit model.