高度时间频率表示和频率交叉信号的即时频率估计
Hui Li1, Xiangxiang Zhu2, Yingfei Wang2
1School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
本研究引入了用于高分辨率时间频率 (TF) 分析和频率交叉信号即时频率 (IF) 估计的新型网络. 该方法提供了强大的噪声免疫力和复杂信号动态的精确表征.
科学领域:
- 信号处理 信号处理
- 机器学习 机器学习
- 应用数学 应用数学 应用数学
背景情况:
- 频率交叉信号在自然现象和工程系统中普遍存在.
- 对于这些信号来说,准确的时间频率 (TF) 表示和瞬时频率 (IF) 估计仍然具有挑战性.
- 现有的方法往往缺乏所需的分辨率和稳定性.
研究的目的:
- 开发一种新的深度学习框架,用于高分辨率TF表示和IF估计频率交叉信号.
- 增强复杂,时间变化的信号特征的分析.
- 为多元组件信号分析提供灵活而准确的方法.
主要方法:
- 提出了一种双网络架构:一个高度的TF代表网络和一个IF分离和估计网络.
- 利用经典的TF分析和U-net技术进行网络构建和培训.
- 纳入了用于灵活组件数的判别模型和用于信号分解和IF估计的分离模型.
主要成果:
- 实现了各种频率交叉信号的高分辨率TF表征.
- 与传统方法相比,证明了强大的噪声免疫力.
- 能够精确估计复杂信号的瞬间频率.
- 在实验验证中表现优于短时间里叶变换,同步挤压变换和卷积神经网络.
结论:
- 拟议的双网络方法有效地解决了分析频率交叉信号的挑战.
- 该方法提供了卓越的TF度和准确的IF估计.
- 这个框架提供了一个强大而精确的工具,用于表征时间变化的信号规律.
相关概念视频
01:18Aliasing
103
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...
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
103
01:10Reconstruction of Signal using Interpolation
151
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...
151
01:11Sampling Continuous Time Signal
185
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...
In the...
185
01:15Sampling Theorem
258
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
258
01:20Frequency Response of a Circuit
205
Inductive circuits present intriguing challenges in electrical engineering, particularly during the transition from the time domain to the frequency domain. This transformation involves converting inductors into impedances and utilizing phasor representation.
The transfer function is pivotal in characterizing how these circuits react to various frequencies, facilitating a profound understanding of their behavior. An essential parameter is the time constant, signifying the...
The transfer function is pivotal in characterizing how these circuits react to various frequencies, facilitating a profound understanding of their behavior. An essential parameter is the time constant, signifying the...
205
01:11Continuous -time Fourier Transform
244
The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
244