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

Scaling01:26

Scaling

243
In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...
243
Properties of Fourier Transform I01:21

Properties of Fourier Transform I

169
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...
169
Basic signals of Fourier Transform01:07

Basic signals of Fourier Transform

485
The Fourier Transform is a pivotal mathematical tool in signal processing, enabling the transformation of time-domain signals into their frequency-domain representations. Among the numerous elements within this domain, certain functions like the sinc function, delta function, and exponential signals hold significant importance due to their unique properties and implications.
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
485
Bode Plots01:26

Bode Plots

619
Bode plots are graphical tools that use logarithmic scales for frequency on the x-axis and gain in decibels on the y-axis. This logarithmic method allows a wide range of frequencies to be compactly displayed, enabling the analysis of component effects on circuit behavior across a broad frequency spectrum.
A network function represents the ratio of a system's output to its input, with the magnitude and phase angle derived from the complex network function. The decibel logarithmic gain is...
619
Exponential Fourier series01:24

Exponential Fourier series

193
In audio signal processing, the exponential Fourier series plays a crucial role in sound synthesis, allowing complex sounds to be broken down into simpler sinusoidal components. This decomposition process is fundamental in analyzing and reconstructing musical notes and other audio signals. The exponential Fourier series expresses periodic signals as the sum of complex exponentials at both positive and negative harmonic frequencies, providing a powerful tool for signal analysis.
Euler's identity...
193
Discrete Fourier Transform01:15

Discrete Fourier Transform

255
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...
255

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

Matched power-frequency-modulated signal transform and its application in bat call signal analysis.

The Journal of the Acoustical Society of America·2024
Same author

Effect of HER2 expression status on the prognosis of patients with HR<sup>+</sup>/HER2<sup>‑</sup> advanced breast cancer undergoing advanced first‑line endocrine therapy.

Oncology letters·2023
Same author

Knowledge-Aided Structured Covariance Matrix Estimator Applied for Radar Sensor Signal Detection.

Sensors (Basel, Switzerland)·2019
Same author

Fusing Infrared and Visible Images of Different Resolutions via Total Variation Model.

Sensors (Basel, Switzerland)·2018
Same journal

Segmental vs phrase-level creak in Polish: An acoustic analysis.

The Journal of the Acoustical Society of America·2026
Same journal

Interaction of near-wall bubble arrays with acoustic waves induced by an oscillating rigid wall.

The Journal of the Acoustical Society of America·2026
Same journal

Ultra-broadband underwater acoustic projector based on transverse resonance orthogonal beam (TROB) mode and acoustic matching layer technique.

The Journal of the Acoustical Society of America·2026
Same journal

Fine-scale quantitative analysis of bowhead whale (Balaena mysticetus) song shows varying stability of song types.

The Journal of the Acoustical Society of America·2026
Same journal

High-resolution depth estimation for multiple wideband sources in deep sea via sparse Bayesian learninga).

The Journal of the Acoustical Society of America·2026
Same journal

Depression markers in speech: An approach based on tract variables dynamics.

The Journal of the Acoustical Society of America·2026
查看所有相关文章

相关实验视频

Updated: Jun 22, 2025

A Computational Method to Quantify Fly Circadian Activity
13:05

A Computational Method to Quantify Fly Circadian Activity

Published on: October 28, 2017

6.0K

使用超级波动尺度变换的超级波动频率调制蝙蝠呼叫的参数估计.

Liang Zhang1, Qinglei Du1

  • 1Department of Early Warning Technology, Air Force Early Warning Academy, Wuhan, 430019, China.

The Journal of the Acoustical Society of America
|July 1, 2024
PubMed
概括
此摘要是机器生成的。

研究人员开发了一个超标尺度转换 (HST) 来分析蝙蝠的呼叫. 这种方法有助于物种识别,并通过准确估计形频率调制信号参数来改进像声纳这样的合成系统.

更多相关视频

Recording Mouse Ultrasonic Vocalizations to Evaluate Social Communication
10:28

Recording Mouse Ultrasonic Vocalizations to Evaluate Social Communication

Published on: June 5, 2016

22.5K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.5K

相关实验视频

Last Updated: Jun 22, 2025

A Computational Method to Quantify Fly Circadian Activity
13:05

A Computational Method to Quantify Fly Circadian Activity

Published on: October 28, 2017

6.0K
Recording Mouse Ultrasonic Vocalizations to Evaluate Social Communication
10:28

Recording Mouse Ultrasonic Vocalizations to Evaluate Social Communication

Published on: June 5, 2016

22.5K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.5K

科学领域:

  • 生物声学是一种生物声学.
  • 信号处理 信号处理
  • 动物沟通动物沟通

背景情况:

  • 呼声定位蝙蝠在不同的狩猎阶段 (搜索,接近,捕获) 修改呼叫波形.
  • 准确估计蝙蝠呼叫参数对于物种识别和人工合成系统 (如雷达,声纳) 的发展至关重要.
  • 许多蝙蝠呼叫表现出高波频调制 (HFM) 信号特征.

研究的目的:

  • 引入一种用于分析HFM模拟蝙蝠呼叫的新方法.
  • 为了能够准确地估计蝙蝠物种识别和技术应用的参数.
  • 将拟议的方法与现有的时间频率分析技术进行比较.

主要方法:

  • 建议使用一个可逆的积分变换,即超标尺度变换 (HST).
  • 在"延迟尺度"域中,HST将蝙蝠呼叫转换为二维峰值.
  • 通过分析这些峰值来进行波分离和参数估计,避免瞬时的频率提取.

主要成果:

  • 该HST方法有效地分析了HFM模拟的蝙蝠呼叫,具有多个波和显著的能量差异.
  • 使用HST进行参数估计更直接,依赖于峰值检测而不是复杂的频率分析.
  • 跨狩猎阶段的波形分析可以减少范围偏差.

结论:

  • 超标尺度转换是分析复杂蝙蝠发声的合适工具.
  • 来自HST分析的估计参数显示了可靠的蝙蝠物种识别的潜力.
  • 在蝙蝠呼叫研究中,HST方法为传统的时间频率分析提供了有利的替代方案.