计算机工程2017，Vol.43Issue(12)：197-202,6.DOI:10.3969/j.issn.1000-3428.2017.12.036
基于脉冲序列合成核的脉冲神经元在线监督学习算法
Online Supervised Learning Algorithm for Spiking Neuron Based on Spiking Sequence Composite Kernel
摘要
Abstract
Spiking neural network uses temporal coding for data processing,which is an effective tool for complex spatial and temporal information processing.In view of this,this paper applies multiple sequence composite kernel into the spiking sequence processing and proposes an online supervised learning algorithm.It uses accumulation and cumulative mechanisms for supervised learning and makes an experiment compared with online PSD algorithm based on single kernel.Experimental results show the better performance of the proposed algorithm.Especially in the performance of larger data sample,it can maintain this excellent performance more significantly.The results also show that the combination of multiple kernel functions can get more stable and efficient spiking sequence composite kernel representation.关键词
脉冲神经元/在线学习/多脉冲序列核/卷积/监督学习Key words
spiking neuron/online learning/multiple spiking sequence kernel/convolution/supervised learning分类
信息技术与安全科学引用本文复制引用
蔺想红,李丹,王向文,张宁..基于脉冲序列合成核的脉冲神经元在线监督学习算法[J].计算机工程,2017,43(12):197-202,6.基金项目
国家自然科学基金(61165002) （61165002）
甘肃省自然科学基金(1506RJZA127) （1506RJZA127）
甘肃省高等学校科研项目(2015A-013). （2015A-013）
