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相关概念视频

Bandpass Sampling01:17

Bandpass Sampling

165
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
165
Upsampling01:22

Upsampling

209
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
209
Aliasing01:18

Aliasing

122
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
122
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

179
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
179
Sampling Theorem01:15

Sampling Theorem

310
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
310
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

215
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
215

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相关实验视频

Updated: Jun 11, 2025

High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis
13:31

High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis

Published on: December 22, 2015

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可重新配置的基于快速频谱传感的数字带宽交叉采样系统.

Li Chen, Peng Ye, Zhixiang Pan

    The Review of scientific instruments
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    PubMed
    概括
    此摘要是机器生成的。

    本研究引入了一种新的可重新配置带宽交叉采集架构,用于提高采样准确性和减少高带宽系统中的数据冗余. 该方法显著改善了信号噪声比和无假动态范围.

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    相关实验视频

    Last Updated: Jun 11, 2025

    High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis
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    Published on: December 22, 2015

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    High-speed Continuous-wave Stimulated Brillouin Scattering Spectrometer for Material Analysis
    07:55

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    科学领域:

    • 电气工程 电气工程
    • 信号处理 信号处理
    • 仪器化 仪器化 仪器化

    背景情况:

    • 平行采集系统中信号带宽的增加挑战了采样精度.
    • 信号通常在频域中表现出稀疏性,这是一种可用于有效获取的特性.

    研究的目的:

    • 提出一个可重新配置的带宽交叉采集架构,以提高测试灵活性和准确性.
    • 为了应对高带宽系统中采样精度的挑战.

    主要方法:

    • 一个两阶段的采样过程:传感和可重新配置的采集.
    • 使用稀疏的里埃转换进行初始光谱传感.
    • 采用根据频谱传感结果的子频段选择和自适应局部振荡器调整.

    主要成果:

    • 在10 GHz采集系统上证明有效,显著减少数据冗余.
    • 与传统带宽交叉系统相比,实现了更好的采集精度.
    • 报告了超过7.4dB的信号噪声比率改进和4.7dB的虚无动态范围改进.

    结论:

    • 拟议的可重新配置的采样方法显著提高了采样结果的质量.
    • 这种架构为准确和灵活的高带宽信号采集提供了可行的解决方案.