摘要
本文设计了一种容易实现的新算法.通过快速稀疏度评估的方法处理稀疏度未知的信号,有效地提高了疏密度评估的效率;同时,在重构过程中,避免了迭代时产生的观测向量的投影运行;此外,应用反应信号可能性的系数,验证了设计算法的性能.当稀疏性相对较大时,论文中所设计的算法的性能将明显下降.
A new algorithm that is easy to implement is designed in this study.The scheme copes with signals of unknown sparsity by means of fast sparsity estimation.Meanwhile,in the process of reconstruction,the projection operation of observation vector during the iteration and further to reduce the complexity of operation is avoided.In addition,the performance of the design algorithm is verified by applying the coefficient of the signal probability and the performance of the algorithm designed will decline significantly when the sparse is relatively large.
作者
李博
李云鹤
李广才
LI Bo;LI Yunhe;LI Guangcai(School of Electronic Information and Mechatronic Engineering, Zhaoqing University, Zhaoqing ,Guangdong 526061,China)
出处
《肇庆学院学报》
2018年第2期7-12,共6页
Journal of Zhaoqing University
基金
广东省自然科学基金博士启动项目(2014A030310286)
关键词
信号修复模型
低能耗
分散式压缩传感
评估系统
a signal reconstruction model
low-power signal
distributed compressed perception
a estimation system
