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相关概念视频

Upsampling01:22

Upsampling

230
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...
230
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

230
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...
230
Aliasing01:18

Aliasing

133
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...
133
Sampling Theorem01:15

Sampling Theorem

329
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.
329
Bandpass Sampling01:17

Bandpass Sampling

174
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....
174
Pulse amplitude and quality01:17

Pulse amplitude and quality

1.7K
Pulse amplitude is a crucial indicator of cardiac health because it provides valuable insights into the strength of left ventricular contractions and the overall uniformity of blood circulation within the vasculature. The strength of the pulse is directly related to the force with which the heart contracts and the volume of blood being pumped.
A weak or absent pulse may indicate reduced cardiac output or poor left ventricular contraction, which can be signs of cardiovascular dysfunction or...
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相关实验视频

Updated: Jun 26, 2025

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脉冲压缩基于形状的ADC/DAC链同步测量算法,具有子采样分辨率.

Xiangyu Hao1, Hongji Fang1, Wei Luo1

  • 1College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China.

Sensors (Basel, Switzerland)
|May 11, 2024
PubMed
概括
此摘要是机器生成的。

本研究提出了一种新的脉冲压缩算法,用于同步模拟到数字 (ADC) 和数字到模拟 (DAC) 转换器链. 该方法实现了分样分辨率,用于在多通道系统中精确的延迟测量.

关键词:
延迟参数测量的测量多通道系统同步多通道系统同步脉冲压缩脉冲的压缩部分抽样解决方案

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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:

  • 在多通道系统中同步多个模拟到数字转换器 (ADC) 和数字到模拟转换器 (DAC) 链是具有挑战性的,因为采样频率限制和组件不一致性.
  • 精确的同步对于复杂的信号处理系统的性能至关重要.

研究的目的:

  • 开发和验证一种新的算法,用于测量和补偿ADC/DAC链中的同步延迟.
  • 为了实现同步与子采样分辨率,提高了多通道系统的精度.

主要方法:

  • 建议使用基于脉冲压缩形状的算法来测量ADC/DAC链的整个延迟参数.
  • 该算法将离散脉冲压缩峰值的形状映射到信号传播延迟上,从而实现子采样分辨率.
  • 在脉冲压缩过程中采用匹配过,以提高噪声性能.

主要成果:

  • 拟议的算法准确地测量了同步差异与子采样分辨率.
  • 该方法在信号噪声比 (SNR) 大于-10dB的场景中显示出强大的性能.
  • 由于其噪声性能,该算法适用于无线通信场景.

结论:

  • 基于脉冲压缩形状的算法为同步多通道ADC/DAC系统提供了精确有效的解决方案.
  • 这种方法克服了传统同步方法的局限性,特别是在杂或复杂的环境中.
  • 获得的分样分辨率提高了多通道信号处理的整体准确性和可靠性.