Adaptive Compressed Sensing via Minimizing Cramer-Rao Bound

作者：Huang Tianyao^*; Liu Yimin; Meng Huadong; Wang Xiqin

来源：IEEE Signal Processing Letters, 2014, 21(3): 270-274.

DOI：10.1109/LSP.2014.2299814

• Adaptive sampling
• compressed sensing
• Cramer-Rao bound
• subspace pursuit

This letter considers the problem of observation strategy design for compressed sensing. An adaptive method, based on Cramer-Rao bound minimization, is proposed to design the sensing matrix. Simulation results demonstrate that the adaptively constructed sensing matrix can lead to much lower recovery errors than those of traditional Gaussian matrices and some existing adaptive approaches.

• 出版日期2014-3
• 单位清华大学