A Distributed Hierarchical Graph Neuron-based Classifier:An Efficient,Low-Computational Classifier

摘要：

Many of the widely used classifiers are time consuming and resource intensive,and hence not practical to be used in the emerging wireless networks.We present an efficient classifier,termed Distributed Hierarchical Graph Neuron(DHGN)-based classifier.Our proposed solution uses a new form of neural network,which consists of a hierarchical graph-based representation of input patterns,and adopts a onecycle learning process.We compare the effectiveness and computational complexity of our proposed classifier with the well known Self-Organizing Map(SOM)classifier in a supervised environment.The results show that the DHGN-based classifier offers lower computational complexity than SOM while guaranteeing satisfactory classification accuracy.

作者: R.A. Raja Mahmood A.H. Muhamad Amin A.I. Khan

作者单位: Clayton School of IT,Monash University Victoria,Australia

会议类型: 国际会议

会议名称: 第一届智能网络与智能系统国际会议(ICINIS 2008)(The First International Conference on Intelligent Networks and Intelligent Systems)

会议地点: 武汉

会议语种:英文

在线出版日期: 2008-11-01（万方平台首次上网日期，不代表论文的发表时间）