Biological Inspired Neural Network Learning and its Application to Data Clustering

摘要：

This paper presents machine learning method of Self organized spiking neural networks. Recently, Spiking Neural Networks have been much considered in an attempt to achieve a more biologically realistic artificial neural network. Spiking neurons with delays to encode the information is suggested. Thus, each output node will produce a different timing which enables competitive learning. The suggested mechanism is designed and analyzed to perform selforganizing learning and preserve the inputs topology. The simulation results show that the model is feasible to perform a self organized unsupervised learning. The mechanism is further assessed in real-world dataset for data clustering problem.

关键词： neural network(NN) Spiking Neural Network(SNN) Self-Organized

作者: MUHAMAD KAMAL M AMIN

作者单位: Electrical and Electronics Engineering Department Kuala Lumpur Infrastructure University College Kajang,Malaysia

会议类型: 国际会议

会议名称: 2011 International Conference on Information System and Computational Intelligence(2011 IEEE信息系统与计算智能国际会议 ICISCI 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 249-253

在线出版日期: 2011-01-18（万方平台首次上网日期，不代表论文的发表时间）