caa a22 4500 606206248 CHVBK 20210128101010.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00034-015-9989-4 doi (NATIONALLICENCE)springer-10.1007/s00034-015-9989-4 Minimum Rate Sampling and Spectrum-Blind Reconstruction in Random Equivalent Sampling [Elektronische Daten] [Yijiu Zhao, Li Wang, Houjun Wang, Changjian Liu] The random equivalent sampling (RES) is a well-known sampling technique that can be used to capture a high-speed repetitive waveform with low sampling rate. In this paper, the feasibility of spectrum-blind multiband signal reconstruction for data sampled from RES is investigated. We propose a RES sampling pattern and its corresponding mathematical model that guarantees well-conditioned reconstruction of multiband signal with unknown spectral support. We give the minimum number of RES acquisitions that hold overwhelming probability to successfully reconstruct original signal. We demonstrate that for signal with specific spectral occupation, the minimum number of RES acquisitions and the minimum sampling rate could be approached. The signal reconstruction is studied in the framework of compressive sampling theory. The eigen-decomposition and minimum description length criteria are adopted to adaptively estimate the dimension of signal, and the number of unknowns of reconstruction problem is reduced. Experimental results are reported to indicate that, for a spectrum-blind sparse multiband signal, the proposed reconstruction algorithm for RES is feasible and robust. Springer Science+Business Media New York, 2015 Compressive sampling nationallicence Random equivalent sampling nationallicence Spectrum-blind reconstruction nationallicence Minimum sampling rate nationallicence Minimum description length nationallicence Zhao Yijiu School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China aut Wang Li School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China aut Wang Houjun School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China aut Liu Changjian School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/8(2015-08-01), 2667-2680 0278-081X 34:8<2667 2015 34 34 https://doi.org/10.1007/s00034-015-9989-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-015-9989-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhao Yijiu School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China aut NATIONALLICENCE 700 1- Wang Li School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China aut NATIONALLICENCE 700 1- Wang Houjun School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China aut NATIONALLICENCE 700 1- Liu Changjian School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/8(2015-08-01), 2667-2680 0278-081X 34:8<2667 2015 34 34