ROBUST ONE-BIT COMPRESSED SENSING WITH PARTIAL CIRCULANT MATRICES
成果类型：
Article
署名作者：
Dirksen, Sjoerd; Mendelson, Shahar
署名单位：
Utrecht University; Australian National University
刊物名称：
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN：
1050-5164
DOI：
10.1214/22-AAP1855
发表日期：
2023
页码：
1874-1903
关键词：
摘要：
We present optimal sample complexity estimates for one-bit compressed sensing problems in a realistic scenario: the procedure uses a structured ma-trix (a randomly subsampled circulant matrix) and is robust to analog pre -quantization noise as well as to adversarial bit corruptions in the quantization process. Our results imply that quantization is not a statistically expensive procedure in the presence of nontrivial analog noise: recovery requires the same sample size one would have needed had the measurement matrix been Gaussian and the noisy analog measurements been given as data.
来源URL：