Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Relation of DFT to z-Transform01:20

Relation of DFT to z-Transform

327
The Discrete Fourier Transform (DFT) is a crucial tool for analyzing the frequency content of discrete-time signals. It converts a sequence of N samples from the time domain into its corresponding sequence in the frequency domain, where each sample represents a specific frequency component.
To understand how the DFT works, it's helpful to consider the z-transform, which is a method for representing discrete sequences in the complex frequency domain. The z-transform involves summing the...
327
Properties of Fourier Transform I01:21

Properties of Fourier Transform I

143
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...
143
Discrete-Time Fourier Series01:20

Discrete-Time Fourier Series

183
The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
183
Discrete-time Fourier transform01:26

Discrete-time Fourier transform

225
The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
One of the notable...
225
Properties of Fourier Transform II01:24

Properties of Fourier Transform II

140
The Fourier Transform (FT) is an essential mathematical tool in signal processing, transforming a time-domain signal into its frequency-domain representation. This transformation elucidates the relationship between time and frequency domains through several properties, each revealing unique aspects of signal behavior.
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
140
Discrete Fourier Transform01:15

Discrete Fourier Transform

188
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
188

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

The effect of ethyl methanesulfonate (EMS) and environmental factors on soybean traits.

BMC plant biology·2025
Same author

Correction: Enhanced DWT-OFDM communication system using wavelet domain equalizer with Co-CFO.

PloS one·2025
Same author

Enhanced hybrid pre-coding and power allocation algorithms for smart irrigation systems using OFDM-based WSNs.

PloS one·2025
Same author

Development of a protocol for whole-lung <i>in vivo</i> lung perfusion-assisted photodynamic therapy using a porcine model.

Journal of biomedical optics·2024
Same author

The combination of postmortem sevoflurane ventilation and in situ topical cooling provides improved 6 hours lung preservation in an uncontrolled DCD porcine model.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation·2024
Same author

Optimizing bandwidth utilization and traffic control in ISP networks for enhanced smart agriculture.

PloS one·2024

相关实验视频

Updated: May 12, 2025

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

9.8K

增强的DWT-OFDM通信系统使用波形域等分器与Co-CFO.

Khaled Ramadan1,2, Emad S Hassan3

  • 1Department of Telecommunication Engineering, Collage of Engineering at Ahlia University, Manama, Bahrain.

PloS one
|April 17, 2025
PubMed
概括

本研究介绍了一种联合低复杂度规范零强制波纹域等级器 (JLCRLZF-WDE),用于多输入-多输出离散波纹转换-直角频率分割多重复合 (MIMO DWT-OFDM) 系统. 新的等分器显著提高了比特错误率 (BER) 性能,并减少了与现有方法相比的模拟时间.

更多相关视频

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

2.9K
Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

2.9K

相关实验视频

Last Updated: May 12, 2025

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

9.8K
Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

2.9K
Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

2.9K

科学领域:

  • 信号处理 信号处理
  • 无线通信无线通信
  • 信息理论 信息理论

背景情况:

  • 基于离散里叶变换 (DFT) 的正交频分割多重复合 (OFDM) 在某些通信场景中面临局限性.
  • 离散波纹转换 (DWT) 为OFDM设计提供了优势,特别是在多输入多输出 (MIMO) 系统中.
  • 现有的均衡技术可能无法充分利用MIMO-OFDM中DWT的优势.

研究的目的:

  • 提出一个新的联合低复杂度规范零强迫波形域等级器 (JLCRLZF-WDE).
  • 通过减少比特错误率 (BER) 和模拟时间来提高MIMO DWT-OFDM系统的性能.
  • 将拟议的等分器与传统的频域等分器 (FDEs) 和波形域等分器 (WDEs) 进行比较.

主要方法:

  • 开发和模拟用于MIMO DWT-OFDM系统的JLCRLZF-WDE.
  • 在共载波频率偏移 (Co-CFO) Rayleigh色通道条件下的性能评估.
  • 与线性零强迫 (LZF) -FDE和线性最小平均平方误差 (LMMSE) -WDE/FDE方案对BER和模拟时间的比较分析.

主要成果:

  • 在JLCRLZF-WDE需要最低额外的信号噪声比 (SNR) (0.82dB在BER=10−3,0.27dB在BER=10−4) 0.82dB在BER=10−4) 匹配LMMSE-WDE的性能.
  • 传统的等分器 (LZF-FDE,LMMSE-FDE) 需要显著更高的SNR (0.31dB到15.35dB的差异).
  • 拟议的方案将模拟时间减少3.17% (相对于LMMSE-WDE) 和12.4% (相对于基于DFT的LMMSE-FDE).

结论:

  • 该JLCRLZF-WDE是MIMO DWT-OFDM系统的高效等效器.
  • 与传统的均等化方法相比,它提供了优越的BER性能和计算效率.
  • 拟议的均衡器为改善无线通信系统性能提供了一个可行的解决方案.