期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：5
页码：1-14
DOI：10.14257/ijsip.2016.9.5.01
出版社：SERSC
摘要：Random equivalent sampling (RES) can composite a waveform with high equivalent sampling rate from multiple low speed sampling sequences. In practical application, the performance of RES signal reconstruction would be degraded by the non-uniform distribution of sampling time. Compressed sensing (CS) theory is adopted to reconstruct RES samples, which could mitigate the inherent coherence of sampling time. However, the CS reconstruction algorithm is sensitive to the signal sparsity level that is unknown in the reconstruction stage. In this paper, we propose a redundancy reduction algorithm for CS base RES signal reconstruction that can ensure reconstruction accuracy while reducing the number of random samples. The experimental results are reported to evaluate the performance of the proposed algorithm.
关键词：random equivalent sampling; compressed sensing; redundancy reduction; ; signal reconstruction
