通信学报2017，Vol.38Issue(9)：95-105,11.DOI:10.11959/j.issn.1000-436x.2017186
RW-MC:基于随机游走的自适应矩阵填充算法
RW-MC: self-adaptive random walk based matrix completion algorithm
摘要
Abstract
Concerning the continually perceiving performance of virtual access points (VAP) was urgent in soft-ware-defined wireless network (SDWN), with the features of VAPs' measurement data (VMD), a self-adaptive matrix completion algorithm based on random walk was proposed, named RW-MC. Firstly, the discrete ratio and covering ratio of VMD account for a sample determination model was used to claim initial samples. Secondly, random walk model was implemented for generating sampling data points in the next iteration. Finally, a self-adaptive sampling redress model concerning the differences between the current error rates and normalize error rates of neighboring completion matrices. The experiments show that the approach can collect the real-time sensory data, meanwhile, maintain a relatively low error rate for a small sampling rate.关键词
SDWN/矩阵填充/RW-MC/随机游走Key words
SDWN/matrix completion/RW-MC/random walk分类
信息技术与安全科学引用本文复制引用
王新恒,王倩云,王佳杰,赵国锋,靳文强..RW-MC:基于随机游走的自适应矩阵填充算法[J].通信学报,2017,38(9):95-105,11.基金项目
国家自然科学基金资助项目( No.61402065 ) （ No.61402065 ）
国家重点基础研究发展计划("973"计划)基金资助项目(No.2012CB315803,No.2012CB315806) The National Natural Science Foundation of China (No.61402065), The National Basic Research Program of China (973 Program) (No.2012CB315803, No.2012CB315806) （"973"计划）
