A Neural Network for Temporal Sequential Information

摘要：

We report a neural network model that is capable of learning arbitrary input sequences quickly and online. It is also capable of completing a sequence upon cueing from any point in the sequence and in the presence of background noise. The architecture of the neural network utilizes sigmoid-pulse generating spiking neurons together with a Hebbian learning rule with synoptic noise.

作者: Adriaan G. Tijsseling Luc Berthouze

作者单位: Cognitive Neuroinformatics Group,Neuroscience Research Institute, AIST,Umezono 1-1-1, Tsukuba 305-8568, JAPAN

会议类型: 国际会议

会议名称: 8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)

会议地点: 上海

会议语种:英文

页码: 1487-1492

在线出版日期: 2001-11-14（万方平台首次上网日期，不代表论文的发表时间）