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Spectra Analysis of Sampling and Reconstructing Continuous Signal Using Hamming Window Function

机译:利用汉明窗函数对连续信号进行采样和重构的频谱分析

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Hamming window function was applied to studying sampling theorem. A continuous band-limited spectrum function F(w) was constructed with Hamming window function. Its corresponding time-domain signal f(t) was worked out by inverse Fourier transform. f(t) was sampled with a comb function dT(t). By modifying the value of T, all kinds of sampling signals were produced, including critical, over and under sampling. With FFT, the frequency spectrum of each sampling signal was figured out. Each spectrum profile was analyzed. The process to reconstruct f(t) was suggested, and the reconstructed results from each of the three kinds of sampling signals were discussed. As the result, critical sampling frequency spectrum in FFT principal value sequence was aliasing at the middle point, over sampling's disconnected, and under sampling's overlapped. The original signal could be accurately reconstructed from over samplings, but couldn't from under one. Hamming window is a perfect model for analyzing and demonstrating the sampling theorem.
机译:汉明窗函数被用于研究采样定理。用汉明窗函数构造一个连续的带限频谱函数F(w)。通过逆傅立叶变换求出其对应的时域信号f(t)。用梳齿函数dT(t)采样f(t)。通过修改T的值,产生了各种采样信号,包括临界,过采样和欠采样。通过FFT,可以得出每个采样信号的频谱。分析了每个光谱图。提出了重建f(t)的过程,并讨论了从三种采样信号中每种信号的重建结果。结果,FFT主值序列中的关键采样频谱在中间点出现混叠,过采样断开,而欠采样重叠。原始信号可以从超采样中准确地重建,但不能从不足一个采样中重建。汉明窗是分析和证明采样定理的理想模型。

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