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

Design Example01:23

Design Example

316
The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
316
Feedback control systems01:26

Feedback control systems

280
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
280
Classification of Signals01:30

Classification of Signals

391
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
391

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

Re-evaluating the Contribution of a Fe-Based Current Collector to Bioelectrochemical Methanogenesis: Role and Mechanisms.

Environmental science & technology·2023
Same author

Integration of proteomics and metabolomics reveals energy and metabolic alterations induced by glucokinase (GCK) partial inactivation in hepatocytes.

Cellular signalling·2023
Same author

Favorable outcomes of front-line risk-adapted therapy in young patients with diffuse large B-cell lymphoma with clinically or biologically high-risk features.

Chinese medical journal·2023
Same author

Comparative efficacy of physical activity types on executive functions in children and adolescents: A network meta-analysis of randomized controlled trials.

Journal of science and medicine in sport·2023
Same author

Resection of intracardiac leiomyoma originating from the inferior vena cava through a single median sternotomy incision using a silk suture snare technique: a case report.

BMC cardiovascular disorders·2023
Same author

Astragalus polysaccharide promotes autophagy and alleviates diabetic nephropathy by targeting the lncRNA Gm41268/PRLR pathway.

Renal failure·2023
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
查看所有相关文章

相关实验视频

Updated: Jun 2, 2025

Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice
08:51

Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice

Published on: May 10, 2019

11.6K

基于IABLN算法在智能系统中的无线通信自动系统的调制模式识别方法.

Ting Xie1, Xing Han2

  • 1Railway Department, Hohhot Vocational College, Hohhot, China.

PloS one
|January 13, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种用于信号调制识别的新型注意网络,通过有效使用时间信息来提高准确性. 这种新方法提高了无线通信系统的识别率.

更多相关视频

Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels
10:00

Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels

Published on: June 2, 2020

20.7K
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

3.0K

相关实验视频

Last Updated: Jun 2, 2025

Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice
08:51

Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice

Published on: May 10, 2019

11.6K
Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels
10:00

Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels

Published on: June 2, 2020

20.7K
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

3.0K

科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 信号处理 信号处理

背景情况:

  • 卷积网络在模块化模式识别的时间信息上扎.
  • 现有的方法对于复杂的调制信号缺乏有效的特征提取.
  • 不高效的识别阻碍了无线通信中的应用.

研究的目的:

  • 开发一种先进的信号调制识别方法.
  • 克服卷积网络在利用时间数据方面的局限性.
  • 为了提高调制模式识别的准确性和效率.

主要方法:

  • 开发了一种双向交互式时间注意网络算法.
  • 利用长短期记忆 (LSTM) 网络来增强时间上下文.
  • 应用软注意力机制用于加权特征提取.

主要成果:

  • 在RML 2016.10b数据集上实现了更高的整体,平均和最大识别率.
  • 显示了92.84%的调制信号识别准确度,卡帕系数增加.
  • 在CSPB.ML2018数据集上展示了0.62的卡帕系数,超过了其他算法.

结论:

  • 拟议的注意力网络显著提高调制信号识别精度.
  • 该方法有效地利用时间信息进行增强的特征提取.
  • 这个算法显示了无线系统中自动调制识别的潜力.