Compressive Sensing Based on Mesoscopic Chaos of Silicon Optomechanical Photonic Crystal
Compressive sensing (CS) is an effective technique that can compress and recover sparse signals below the Nyquist-Shannon sampling theorem restriction. In this study, we successfully realize CS based on the mesoscopic chaos of an integrated Si optomechanical photonic crystal micro-cavity, which is f...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9201125/ |
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| Summary: | Compressive sensing (CS) is an effective technique that can compress and recover sparse signals below the Nyquist-Shannon sampling theorem restriction. In this study, we successfully realize CS based on the mesoscopic chaos of an integrated Si optomechanical photonic crystal micro-cavity, which is fully compatible with the complementary metal-oxide-semiconductor (CMOS) process. Using the sensing matrix, we tested one-dimensional waveforms and two-dimensional images. The ultimate recovery curves were determined by comparing the chaotic sensing matrix with the Gaussian, Toeplitz, and Bernoulli matrices. Our results could pave the way for future large-scale implementations of high-speed CS processes based on fully CMOS-compatible Si-micro-cavities. |
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| ISSN: | 1943-0655 |