低复杂度压缩感知中的快速观测方法

doi:10.3969/j.issn.1001-2400.2017.01.019

Abstract

Abstract:

The random sensing algorithms are hard for hardware implementation while the deterministic sensing algorithms have difficulty in acquiring large signals in the sensing systems of compressive sensing. This paper proposes a fast sensing method for compressive sensing with low complexity. The input signal is firstly permuted by an m-sequence controlled interleaving device. Then the permuted signal is transformed by the fast Walsh-Hadamard transform and down sampled to generate the measurements. Theoretical analysis indicates that the entries of the corresponding sensing matrices are asymptotically normally distributed. Simulation results show that the sensing performance of the corresponding matrices is almost the same as that of completely random sensing operators with a shorter computational time cost. The proposed method has good sensing performance and is easier for hardware implementation, which is meaningful in practice.

Key words: compressive sensing, fast sensing, low-complexity, m-sequence

QUAN Lei;XIAO Song;XUE Xiao;LI Ying. Fast sensing method in compressive sensing with low complexity[J].Journal of Xidian University, 2017, 44(1): 106-111.

References

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Fast sensing method in compressive sensing with low complexity

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