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- 저자 : Yijiu Zhao (검색결과 2 건)
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A Random Sequence Generation Method for Random Demodulation Based Compressive Sampling System
Li Wang,Yijiu Zhao,Zhijian Dai 보안공학연구지원센터(IJSIP) 2015 International Journal of Signal Processing, Image Vol.8 No.1
Random demodulation based compressive sampling technique is a novel approach that it can break through the Shannon sampling theorem for the sparse signal capturing. A major challenge in the random demodulation based sampling system is the random sequence generation. In this paper, we introduce an approach to generate the high-speed random sequence that meets the incoherence of compressive sampling. The proposed technique employs a field programmable gate array (FPGA). First, the random sequence is parallel stored in the memory of FPGA, and it is read out byte by byte using a low speed clock. Second, the low-speed byte sequence is converted to a high-speed bit sequence by a circuitry. This proposed approach can program the random sequence dynamically without making any change to the circuitry system. Experimental results indicate that, the random sequence generated by the proposed approach is feasible to sensing the signal, and the constructed system can compressively sample and reconstruct the sparse signal.
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Redundancy Reduction for Compressed Sensing based Random Equivalent Sampling Signal Reconstruction
Jianguo Huang,Li Wang,Yijiu Zhao 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.5
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.
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