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Surpassing the Nyquist Sampling Limit via Postmodulation
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AI
DOI：10.1103/PhysRevApplied.18.034077.png)
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Surpassing the Nyquist sampling limit to avoid aliasing distortion is an important issue for the task of time-varying parameter estimation. To achieve this goal, we propose a high-precision time-varying param-eter estimation scheme based on split detection and postmodulation of light instead of postprocessing of data. Theoretical analysis demonstrates its advantage of surpassing the Nyquist sampling limit and the avoidance of anti-aliasing distortion. In order to illustrate the feasibility, a numerical simulation based on the acceptance rejection sampling method is performed showing the noise robustness of the scheme in terms of correlation coefficient, root-mean-square error, and mean absolute error. Our scheme provides a method for function estimation.
Keyword:
RECONSTRUCTION
SIGNALS
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IF:
4.4
论文数:
7.1K
被引数:
2.8W
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