【摘要】 以HindmarshRose(HR)神经元组成网络,研究这些网络的记忆(或模式)存储与时间分割问题.给定一个输入模式,它是几种模式的叠加,网络能够以一部分神经元同步发放的形式一个接一个地分割出每一种模式.如果输入的模式是缺损的,系统能够恢复为原型,即网络具有联想记忆功能.模拟也得到据作者所知至今还未报道的一些现象.更多还原

【Abstract】 We present in this paper some results on the temporal segmentation and retrieval of stored memories or patterns using neural networks composed of the widely used model neurons, the Hindmarsh-Rose neurons. For an input pattern which is an overlapped superposition of several stored patterns, it is shown that the proposed neuronal network model is capable of segmenting out each pattern one after another as synchronous firings of a subgroup of neurons. If a corrupted input pattern is presented, the network is able to retrieve the perfect one, i.e., it has the function of associative memory. Some new phenomena in our simulation are found that have not been reported elsewhere in our knowledge.更多还原