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相关概念视频

Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

13.7K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
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Fast Fourier Transform01:10

Fast Fourier Transform

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The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
270
Power Factor Correction01:20

Power Factor Correction

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The power transmission to a factory involves the transfer of apparent power, a combination of active and reactive power. The power factor measures how effectively electrical power is converted into useful work output. The ratio of the real power (KW) that does the work to the apparent power (KVA) supplied to the circuit.
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Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

64
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,...
64
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

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In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
231
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

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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....
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相关实验视频

Updated: Jun 6, 2025

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
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Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

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光学矩阵计算用于光学前向错误校正编码.

Tianyan Guo, Jiangbing Du, Wenjia Zhang

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    概括
    此摘要是机器生成的。

    本研究介绍了使用光学矩阵计算的光学前向错误校正 (FEC) 编码器. 它实现了有效的错误校正与显著的净收益,降低了光通信中的延迟和成本.

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    相关实验视频

    Last Updated: Jun 6, 2025

    Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
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    Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

    Published on: March 20, 2017

    9.8K
    Bringing the Visible Universe into Focus with Robo-AO
    10:35

    Bringing the Visible Universe into Focus with Robo-AO

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    科学领域:

    • 光学通信是指光学通信.
    • 信息理论 信息理论
    • 摄影工程工程 摄影工程

    背景情况:

    • 在通信系统中,前向错误校正 (FEC) 的电子实现是标准.
    • 光通信需要即时光学处理,以最大限度地减少光电光学 (OEO) 转换,减少延迟和成本.

    研究的目的:

    • 为了展示一个光学FEC编码方法的概念验证.
    • 通过集成光学处理来减少光通信系统中的OEO转换.

    主要方法:

    • 使用光学矩阵计算与波长分割复杂化 (WDM).
    • 采用时间波长交叉操作用于光学信号处理.
    • 使用光纤设备开发了一种光学FEC编码器.

    主要成果:

    • 与理论电气编码器相比,实现了与理论电气编码器相比几乎相当的净编码收益.
    • 在20 Gb/s开关键化 (OOK) 传输中,证明了有效的错误校正,净收益为2 dB.
    • 验证了传输-计算-合并系统的可行性.

    结论:

    • 拟议的光学FEC方法有效地纠正光学传输中的错误.
    • 该技术支持FEC的完整实现,包括编码和解码.
    • 这种方法为通信系统中集成光学处理铺平了道路.