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相关概念视频

Upsampling01:22

Upsampling

236
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...
236
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

195
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...
195
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

89
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
89
Aliasing01:18

Aliasing

136
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...
136
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

81
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
81
Second-order Op Amp Circuits01:19

Second-order Op Amp Circuits

346
Implementing second-order low-pass filters in audio systems is crucial in refining audio signals by eliminating undesirable high-frequency noise. These filters typically involve second-order op-amp circuits configured as voltage followers, encompassing two nodes with distinct storage elements.
The analysis of such circuits follows a systematic approach, similar to the second-order RLC circuits. In practical scenarios, bulky inductors are rarely employed due to their size and weight. This means...
346

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相关实验视频

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X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
08:30

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

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低复杂性和低延迟等效技术 - - 概率式噪声消除技术.

Nebojša Stojanović, Youxi Lin, Talha Rahman

    Optics express
    |March 5, 2024
    PubMed
    概括

    数据中心的光学链接将越来越多地使用四级脉冲振幅调制 (PAM4) 收发器. 一个新的概率噪声消除 (PNC) 算法为数据中心网络 (DCN) 中的数字信号处理 (DSP) 提供了更好的性能.

    科学领域:

    • 光学通信是指光学通信的应用.
    • 数据中心网络数据中心网络.
    • 数字信号处理是数字信号处理.

    背景情况:

    • 具有四级脉冲振幅调制 (PAM4) 的强度调制和直接检测 (IMDD) 系统被设置为主导数据中心 (DC) 和短距离光学链路.
    • 未来的100Gbaud PAM4收发器需要先进的数字信号处理 (DSP) 和前置错误校正 (FEC) 代码.
    • 带宽限制挑战了传统的DSP,需要从线性前均等器 (FFE) 升级到更复杂的算法,如Volterra均等器,最大概率序列估计 (MLSE) 或最大后期概率 (MAP).

    研究的目的:

    • 为数据中心网络 (DCN) 引入一种新的,低复杂度,低延迟的等分算法.
    • 为了解决复杂的DSP算法的局限性,如决策反均衡器 (DFE) 和MLSE/MAP,由于DCN中的功率和延迟限制.
    • 为了提高光学收发器在带宽有限的环境中的性能.

    主要方法:

    • 开发了一种名为概率噪声取消 (PNC) 的新型前均衡算法.
    • 在带宽限制下,PNC算法根据它们的概率权衡噪声模式.
    • 有效地纠正由送等效器 (FFE) 中噪声染色引起的相关错误.

    主要成果:

    • 拟议的PNC算法在DFE和MLSE之间实现了性能.

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  • 它为DCN中的DSP提供了低复杂度和低延迟的解决方案.
  • 在带宽有限的频道中,通过噪声染色引发的错误的有效纠正.
  • 结论:

    • 在下一代数据中心收发器中,PNC算法为先进的DSP提供了可行的替代方案.
    • 它符合DCN的严格功耗和延迟要求.
    • PNC提高了在带宽限制下运行的光学链路的可靠性.