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

Encoding01:19

Encoding

208
Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
208
Deconvolution01:20

Deconvolution

197
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
197
Aliasing01:18

Aliasing

163
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...
163
Block Diagram Reduction01:22

Block Diagram Reduction

248
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
248
Basic Discrete Time Signals01:16

Basic Discrete Time Signals

240
The unit step sequence is defined as 1 for zero and positive values of the integer n. This sequence can be graphically displayed using a set of eight sample points, showing a step function starting from n=0 and remaining constant thereafter.
The unit impulse or sample sequence is mathematically expressed as zero for all n values except at n=0, where it is one. The unit impulse sequence, denoted by δ(n), is the first difference of the unit step sequence, while the unit step sequence u(n) is...
240
Bewley Lattice Diagram01:12

Bewley Lattice Diagram

764
The Bewley lattice diagram, developed by L. V. Bewley, effectively organizes the reflections occurring during transmission-line transients. It visually represents how voltage waves propagate and reflect within a transmission line, making it easier to understand the complex interactions that occur.
764

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

High-Throughput Polar Code Decoders with Information Bottleneck Quantization.

Entropy (Basel, Switzerland)·2024
Same author

Semantic Information Recovery in Wireless Networks.

Sensors (Basel, Switzerland)·2023
Same author

Multidimensional Minimum Euclidean Distance Approach Using Radar Reflectivities for Oil Slick Thickness Estimation.

Sensors (Basel, Switzerland)·2022
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jul 24, 2025

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.9K

最小整数计算有限字母信息传递解码器:从理论到解码器实现朝着1 Tb/s的方向

Tobias Monsees1, Oliver Griebel2, Matthias Herrmann2

  • 1Department of Communications Engineering, University of Bremen, 28359 Bremen, Germany.

Entropy (Basel, Switzerland)
|July 8, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了低密度平价检查 (LDPC) 代码的最小整数计算 (MIC) 解码器,以减少复杂性实现高通信性能. 新型MIC解码器与高通量应用的现有方法相比,提供了更高的效率和性能.

关键词:
这是一个LDPC代码.解码的解码方法是有限字母的消息传递传递.实施效率 实施效率 实施效率信息瓶信息瓶是指一个信息瓶.

更多相关视频

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.0K
P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

617

相关实验视频

Last Updated: Jul 24, 2025

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.9K
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.0K
P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

617

科学领域:

  • 数字通信数字通信
  • 错误纠正编码 错误纠正编码
  • 在 VLSI 设计中,

背景情况:

  • 在低密度平价检查 (LDPC) 代码中的消息传递 (MP) 解码涉及检查节点 (CN) 和变量节点 (VN) 之间的外部信息交换.
  • 实际实现面临由于消息定量化的局限性,通常使用少量的比特.
  • 有限字母信息传递 (FA-MP) 解码器旨在以低位精度最大化相互信息 (MI),接近高精度信念传播 (BP) 性能.

研究的目的:

  • 为LDPC代码开发一种新的最小整数计算 (MIC) 解码器设计.
  • 用高效的低位整数计算取代复杂的多维查找表 (mLUT).
  • 为了实现与mLUT解码器相当的通信性能,实现复杂性要低得多.

主要方法:

  • 利用相互信息最大化量化信念传播 (MIM-QBP) 和重建计算量化 (RCQ) 的框架.
  • 使用Log-Likelihood Ratio (LLR) 分离属性用于信息最大化的量化器.
  • 导出比特分辨率的标准,以准确地表示mLUT映射,并实施低位整数计算.

主要成果:

  • 该MIC解码器实现了对应的mLUT解码器的确切通信性能.
  • 与基于mLUT的解码器相比,其实现复杂性明显较低.
  • 在28纳米FD-SOI技术的路由复杂性,面积和能源效率方面超过了以前的FA-MP和Min-Sum (MS) 解码器.

结论:

  • MIC解码器为LDPC解码提供了高效的解决方案,平衡性能和复杂性.
  • 这种设计适用于高通量应用,例如需要高达1 Tb/s的应用.
  • MIC解码器代表了节能和面积高效的数字通信系统的重大进步.