VECTOR APPROXIMATE MESSAGE PASSING FOR QUANTIZED COMPRESSED SENSING

被引：0
|
作者：
Franz, Daniel [1 ]
Kuehn, Volker [1 ]
机构：
[1] Univ Rostock, Inst Commun Engn, Rostock, Germany
来源：
2018 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2018) | 2018年
关键词：
approximate message passing; generalized linear model; quantized compressed sensing; estimation theory;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In recent years approximate message passing algorithms have gained a lot of attention and different versions have been proposed for coping with various system models. This paper focuses on vector approximate message passing (VAMP) for generalized linear models. While this algorithm is originally derived from a message passing point of view, we will review it from an estimation theory perspective and afterwards adapt it for a quantized compressed sensing application. Finally, numerical results are presented to evaluate the performance of the algorithm.
引用
收藏
页码：341 / 345
页数：5
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