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相关概念视频

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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Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

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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,...
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Properties of Fourier Transform I01:21

Properties of Fourier Transform I

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The application of Fourier Transform properties in radio broadcasting is multifaceted, enabling significant advancements in the way signals are transmitted and received. Key areas where these properties are utilized include simultaneous multi-channel transmission, audio clip speed adjustments, live broadcast delays for different time zones, audio frequency adjustments, and signal demodulation.
In radio broadcasting, multiple audio signals often need to be transmitted simultaneously. The Fourier...
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Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

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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...
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Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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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...
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Bandpass Sampling01:17

Bandpass Sampling

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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....
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相关实验视频

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Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
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预期-最大化向量近似消息传递为基础的频域轮方程,用于水下声通信.

Xinrui Zhang1, Jun Tao1, Dong Li2

  • 1Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education, School of Information Science and Engineering, Southeast University, Nanjing 210096, China.

The Journal of the Acoustical Society of America
|November 21, 2023
PubMed
概括

这项研究引入了用于水下声通信的增强频域轮均衡 (FDTE). 新方法在平衡过程中学习噪声功率,在动态环境中提高性能.

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科学领域:

  • 信号处理 信号处理
  • 水下通信是指水下通信.

背景情况:

  • 道平衡对于单载波水下声学 (UWA) 通信至关重要.
  • 现有的向量近似传递信息的频域轮均衡 (VAMP-FDTE) 需要预先确定的噪声功率,这在动态的UWA环境中具有挑战性.

研究的目的:

  • 开发一个增强的VAMP-FDTE方案,在线学习噪声功率.
  • 提高UWA通信系统的稳定性和性能.

主要方法:

  • 提出了一种增强的VAMP-FDTE方案,其中包括预期最大化 (EM) 算法用于在线噪声功率估计.
  • 利用VAMP-FDTE的中间结果来实现基于EM的噪声功率学习,并尽量减少额外的计算开销.

主要成果:

  • 改进的VAMP-FDTE,命名为EM-VAMP-FDTE,与标准的VAMP-FDTE相比,表现出更高的性能.
  • 使用MIMO配置进行浅海水平UWA通信试验的实验数据验证了性能改进.

结论:

  • 通过EM算法在线噪声功率学习显著提高了UWA通信中的VAMP-FDTE性能.
  • 对于面临未知和动态噪声条件的UWA系统,EM-VAMP-FDTE方案提供了一个实用的解决方案.